Cultural Transmission and Lithic Technology in Middle Stone Age Eastern Africa

by Kathryn L. Ranhorn

B.A. in Anthropology, May 2010, University of Florida

A Dissertation submitted to

The Faculty of The Columbian College of Arts and Sciences of The George Washington University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

August 31, 2017

Dissertation directed by

Alison S. Brooks Professor of Anthropology and International Affairs

David R. Braun Associate Professor of Anthropology

The Columbian College of Arts and Sciences of The George Washington University certifies that Kathryn L. Ranhorn has passed the Final Examination for the degree of

Doctor of Philosophy as of May 9th, 2017. This is the final and approved form of the dissertation.

Cultural Transmission and Lithic Technology in Middle Stone Age Eastern Africa

Kathryn L. Ranhorn

Dissertation Research Committee:

Alison S. Brooks, Professor of Anthropology and International Affairs, Dissertation Co-Director

David R. Braun, Associate Professor of Anthropology, Dissertation Co-Director

Francys Subiaul, Associate Professor of Speech, Language, and Hearing Sciences, Committee Member

Christian A. Tryon, Associate Professor of Anthropology, Harvard University Committee Member

iii Dedication

To my mother, who taught me that evolution requires sometimes copying old ideas, and often creating new ones.

Na pia kwa marafiki wangu wa Tanzania na Kenya, hii ndo story zenu. Bado tunapanda.

“It sometimes appears that all of us treat stone artifacts as infinitely complex repositories of paleocultural information and assume that it is only the imperfections of our present analytical systems that prevent us from decoding them. But is this really so?” (Isaac 1977:207)

iv Acknowledgements

The completion of this work was itself a journey, and it is impossible to name all

of the people who played a role in it. I first must thank Dr. Alison S. Brooks, whose

unabashed faith in my abilities enabled me to reach ever higher, and whose very

existence served as an ever-present reminder that women archaeologists are a force to be

reckoned with. I remember the first time we met, at Olorgesailie in southern Kenya. I

arrived via public matatu, traveling alone from Nairobi, having taken a 14-hour bus ride

from Dar es Salaam the day prior. Despite my having a background in cultural anthropology, Alison accepted me into a graduate program in paleobiology with the adage, “You understand Africa and want to learn more. That’s the big thing. Everything else, you will learn in graduate school.” Alison’s encyclopedic, inquisitive, and analytical mind inspired the undertaking of this research, and immensely added to the completion of it. To this day I can go to Alison with a question as simple as, “What is the oldest known symbolic use of feathers?” Approximately 45 minutes later we will depart, having discussed the site, publication, and stratigraphy of the relevant evidence, and also how these disparate parts fit into the whole of human behavioral evolution. Alison, thank you for being my sensei.

Secondly I thank Dr. David Braun, for his eager willingness to collaborate and incorporate me into the Koobi Fora Field School, his patience as I learned the ins and outs of Paleolithic research, and his advice, both in the field and in the lab. Shooting in ancient footprints at Ileret, setting up a grid on a rapidly eroding sand dune, and watching our field school students academically progress are just a few highlights of my collaborations with Dave. He taught me to “walk the walk” in the collection of

v archaeological data. From the maintenance of Land Rovers to the leveling of a total

station, from student recruitment to a 50-person bush camp, I witnessed every piece of

data come together. I look forward to many more years of dust and diesel with Dave.

I would not be remotely involved in paleoanthropology were it not for Dr. Fidelis

Masao at the University of Dar es Salaam. I was 19 years old when I walked into his

office and asked if it was ‘too late’ to register for his class, Archaeological Methods. A

week into the course he informed our class about his field school at Olduvai Gorge, and

he again accepted when I pleaded to join. My decision to come to graduate school and

study human origins was made two years later, at chini ya mti in Leakey Camp, as Fidelis

explained to me the potential for Middle Stone Age archaeology in Tanzania. I later

returned to Olduvai to study Nasera, sleeping in Mary Leakey’s old room at night and

measuring intractable quartz by day, all of which was organized by Fidelis. “Faza” has

trained an army of Tanzanian archaeologists, and I hope to carry on his torch.

My dissertation committee is a tour de force of human behavioral evolution and

each member played an integral role. Francys Subiaul inspired me to pursue social

learning as a science. His passion for his research transmits to his students, and every

meeting we had led to ideas for more experiments. The social learning flint knapping

component of this dissertation is central to the inferences made about the archaeological

record, and none of it would have been possible without Francys Subiaul.

Tyler Faith joined the committee later in the game and provided objective,

crystal-clear and constructive criticisms on the research questions, methods, and statistical analyses. Tyler is an ‘ace in the hole’ for any Paleolithic project and I look forward to future collaborations with him. Matthew Douglass also joined the committee

vi relatively late, and his perspective on living populations, actualism, reduction sequences, and non-lineal approaches to behavioral evolution all contributed to this thesis.

Finally, Christian Tryon has been my bulldog since before my acceptance into graduate school. Whenever “imposter syndrome” crept in, Christian was there, asking for my opinion on artifacts and treating me as a scholar and collaborator. Working with

Christian and Jason Lewis at Kisese II provided a much-needed breath of fresh air, a reminder that solid Middle Stone Age research can, and should, be systematically conducted in Tanzania. Our future research agenda at Kisese II is the number one reason that I was able to finish this dissertation, knowing that something even more fascinating awaits on the horizon in a painted rock shelter.

The Center for the Advanced Study of Human Paleobiology (CASHP) has been my academic home for six years, and, given the choice, I would not have attended any other program. Bernard Wood served as an ever-present hypothesis-testing guardian angel on my shoulder, constantly checking that my research was ‘big’ enough to make a difference and ‘sound’ enough to be taken seriously. I, and countless others, also applaud

Bernard for his public dismissal of sexual harassment in our field. Chet Sherwood,

Shannon McFarlin, and Carson Murray all provided listening ears over countless coffees while I navigated the winding road of graduate school. Carson made a dream come true when she invited me to Gombe with Susana Carvalho. Observing chimpanzees as they fished for termites, followed by sunset cocktails with Jane Goodall, remain highlights of my career. From an analytical perspective, Mark Grabowski and Andrew Barr taught me everything I know about R and statistics—knowledge that I use every single day.

vii One main reason that I love CASHP is that it is housed within the Department of

Anthropology. At any point I could walk over to the Hortense Amsterdam House, play

with the department’s pet dog, and talk about various topics tangential to my research,

like the use of mobile phones as a source for sustainable development in Kenya. The

whole of the Anthropology department has shaped my scholarship, and provided a template for my future career goals. Jonathan Higman, Cortnie Cogan, Charlotte Krohn,

Keely Arbenz-Smith, and the rest of the administration team do the work of saints, from

fixing course registration to processing receipts written in Swahili on a napkin. I

appreciate them all.

My fellow graduate students at CASHP also deserve special mention. Andrew

Zipkin was easily the best ‘academic older brother’ that a student could ask for. He

consistently checked in on me, celebrated with me as I passed qualifying exams, and

advised me when I was lost. He helped me navigate the chaos of academic conferences,

from Memphis to Hawaii, Orlando to Vancouver. Amy Bauernfeind, Elizabeth Renner,

and Habiba Chirchir all provided years of mental and emotional support, often in the dark

confines of local pubs. One of my proudest accomplishments in graduate school came

from these discussions: our launching of CASHP Women in Science (also known as

Diversity in Science or DIS). Kevin Hatala, Andrew Du, and Kes Schroer all provided

helpful ‘older sibling’ support consistently throughout graduate school. Finally, David

Patterson was an attentive soundboard for hundreds of hours, and offered friendship,

advice, and a cold beer when needed, both in DC and in the field. I am privileged to

know so many talented scientists, to have come of age with them academically, and to

viii continue to learn from them every day, especially as I embark on my post-graduate career trajectory.

My involvement with the Koobi Fora Field School was the most formative experience of my graduate career. Kathryn Braun goes unacknowledged too often, and yet the field school would not exist without her strength, organization, patience, and kindness. Emmanuel Ndiema not only oversees affiliation letters, export permit requests, and curation of archaeological materials, he also personally escorted me to archaeological sites at East Turkana. His willingness to collaborate and his knowledge of the Holocene, as well as local populations, have improved my research immensely. David Kipkebut,

Ben Sila, and Peter Onyango are not only ‘surgeons of dirt,’—having moved more sediment than a flash flood—their kind spirits, positive attitudes, and comical approaches to fieldwork were the main reason I came back every year. Musango and Phillipine, and the entire support staff at KFFS, all deserve a raise—they have shed more sweat than any of us. I would not have survived long dusty Karari nights without Sarah Hlubik, who brings with her not only extra tent stakes, band-aids, bruntons, and twine, but also a lust for fieldwork and excavation unlike any I’ve ever seen. Her love for archaeology is contagious. Steven Merritt, Russell Cutts, and Jonathan Reeves made fieldwork fun, and each provided a unique perspective on Paleolithic behavior that shaped my research.

I am lucky to have collaborated with several scientists outside of CASHP. Other than Koobi Fora, formative experiences of my graduate career were lab rotations at

Pinnacle Point, South Africa and Les Eyzies, France. In France, Jacques Pelegrin and

Pierre Jean Texier not only taught me about chaîne opératoire, they demonstrated it, with dozens of hours of flintknapping. This experience launched my interest in experimental

ix knapping and primitive technology. Also in France, Roland Nespoulet invited me to

excavate at Abri Pataud. Excavating os brûlé and silex at the same site where Alison conducted her own dissertation became my personal Paleolithic pilgrimage, and juxtaposed nicely with my experiences in Africa. The Pataud team’s tours to the dozens of nearby rock art sites in Les Eyzies left me speechless, and sparked my interest in rock art that continues to develop today. In many ways, my French collaborators have shaped my future plans in central Tanzania, and I thank them for their hospitality and kindness.

At Pinnacle Point, Curtis Marean kindly invited me to join the lithics team for a

marathon analysis of the PP5-6 sequence. Jayne Wilkins led the effort, and taught me

how to transform a cave full of artifacts into a database of measureable observations.

Jayne’s organized and systematic approach, particularly her use of E4, substantially

contributed to my own data collection methods. The entire lithic analysis team—Simen

Oestmo, Telmo Pereira, Jayne Wilkins, and Ben Schoville—all have a contagious passion

for understanding past behavior, and I thank them for including me on this project. Curtis

Marean has provided helpful career advice since 2011, and he remains one of my go-to advisors when planning long-term and short-term archaeological agendas. I hope to create in Tanzania what Curtis has created at Pinnacle Point, and his mentorship has helped me make that a reality.

I also thank Rick Potts at the Smithsonian Institution for inviting me to

Olorgesailie before I even entered graduate school. His research program at Olorgesailie is impressive from both a logistics and data collection perspective. I learned from Rick the adage, “If you keep the researchers happy, they will do good research.” I apply this to my logistical planning daily. John Yellen is a joy to work with, both in the field and in

x DC, and his insightful comments and advice have influenced my scholarship immensely.

I will always remember our first survey in southern Tanzania. Briana Pobiner not only

welcomed me to Kenya for the first time on my way to Olorgesailie, she has also been a

role model and close friend throughout my career. Kay Behrensmeyer is a geology- taphonomy-paleontology goddess among mortals, and is also a great friend. When I am at

a loss for what to do, particularly mid-season at Koobi Fora, I ask myself, WWKD?—

“What would Kay do?”. It was this question that led me to collaborate with Silindokuhle

Mavuso, one of the most talented geologists I have met, and one of my best friends. I thank Silindo for every single section he has drawn for my research, and for every time he made me laugh.

When the going got rough, Katie Hinde was there. I cannot acknowledge Katie enough for her mentorship. She somehow finds the time to respond to my messages within seconds, providing thought out, informed advice, and offering to take immediate action if necessary. From Harvard to New Orleans, she provided a listening ear when I needed one. Thank you Katie, for being fearless, smart, and heartfelt.

My research would not have been possible without financial support from several agencies. I benefitted immensely as an undergraduate from the Florida Bright Futures

Scholarship Program, and the Ronald E. McNair Scholars Program. The National Science

Foundation’s Integrative Graduate Education and Research Traineeship (IGERT) program enabled me go from a low-income undergraduate to a financially stable graduate student in Washington, DC. Early grants from the Cosmos Club, Explorers Club

Washington Group, and Cotlow Fund launched my graduate research and gave me validation as a young scholar. Fulbright-Hays enabled me to live in Tanzania for over 12

xi months, collecting the bulk of my dissertation data, and explore the next steps in my research career. The Wenner Gren Foundation and Leakey Foundation both graciously supported me, enabling me to launch the Koobi Fora Middle Stone Age project, and ultimately, to finish my dissertation research. I am thankful for all of this financial support.

The majority of these data were collected at the National Museum of Kenya in

Nairobi. I am thankful to all of the NMK Archaeology staff for assisting my lithic analysis research, housing my Koobi Fora collections, and assisting with export of materials. In Tanzania, the Commission on Science and Technology (COSTECH) has provided quick and helpful assistance for several years. I thank the Department of

Antiquities, particularly Sikujua Ramadhani, for working to secure our sites and archaeological finds. Finally I thank the National Museum of Tanzania, particularly Dr.

Audax Mabulla, Dr. Agness Gidna and Dr. Amandus Kweka, for hosting and assisting me for all these years.

I had the fortune of meeting Matthew Knisley and Andrew Harvey in Tanzania in the midst of fieldwork. They are brilliant scholars and close friends, and they have opened my world to the multiple layers of history that characterize Tanzania’s recent past. I look forward to unraveling these layers together. The Mwenge Woodcarvers

Market and English Class have been my Tanzanian family for nearly ten years. I would not speak Swahili or understand the nuances of street slang were it not for Mwenge. My heart will always be there. Rajabu Haji, Elias Clemenc, and Kevin Tiago Patrick particularly, you make me so proud. Your undying hustle to achieve your dreams inspires me to work harder every day.

xii I simply would not have a heart for exploration, nor a mind for analysis, were it

not for my family. My mom bought me my first telescope, handed me my first Carl

Sagan book, and ensured that I knew how to change a tire and balance a checkbook

before age 12. My brother Donnie gave me the tough outer skin I needed to survive in

this field, and always treated me like one of the guys. I thank my family for the sacrifices

they made every single year for my career, particularly when I ‘left for Africa for months

on end,’ or when I missed Christmas for fieldwork. Thank you for your love and support.

Lastly, I thank Rutger Jansma, my stable canoe on a choppy sea. Thank you for

navigating the waves with love, respect, understanding, and most of all, a wanderlust that parallels only my own. I look forward to a lifetime of discovery with you.

xiii Abstract of Dissertation

Cultural Transmission and Lithic Technology in Middle Stone Age Eastern Africa

This dissertation sought to build a ground-up understanding of how cultural

transmission can be studied in Paleolithic assemblages, with a focus on Middle Stone

Age eastern Africa. Cultural transmission here refers to the process by which ideas,

innovations, or technologies are transmitted across individuals. Similarities in

technological patterns at Middle Stone Age (MSA) archaeological sites are thought to represent regional networks of such transmission. These patterns of technology have been interpreted as representing the earliest forms of regional identity, in which human social networks were territorial and hyper-prosocial. The overarching goal of this dissertation was to test to what extent regional patterns in MSA stone tool technology could be explained variously by cultural transmission or functional concerns (e.g. raw material constraints). In order to accomplish this, experimental proxies were developed to better understand how cultural transmission is embedded in stone tool technology, and these proxies were then studied at multiple MSA localities in Kenya and Tanzania.

The first phase of this dissertation asked the question, “What aspects of

Paleolithic assemblages do we measure to study cultural transmission?” Social learning flintknapping experiments were conducted to determine what, if any, empirical traces of cultural transmission can be detected in stone artifacts. Discerning which lithic signatures are related to transmission can shed light on the processes by which technological variability forms. To do this, flint knappers created stone tools under two controlled conditions of cultural transmission: emulation and imitation. Knappers also made stone

xiv tools without any cultural transmission, forming a control group. Following the

experiments, the lithic assemblages were measured and analyzed; thus the question

became: given a known state of cultural transmission (no transmission, imitation, or

emulation), which measurements best predict the experimental condition? Standardized

porcelain cobbles were created to control the effects of size and shape on lithic

variability. It was demonstrated that variables associated with core reduction strategy are

more strongly associated with cultural transmission than variables associated with flake

morphology, which are highly susceptible to equifinality.

The second phase of this dissertation asked the question, “How can core reduction

strategy be measured?” Three-dimensional photogrammetry was used to develop new

methods to quantify strategies of core reduction. To do this, technologically defined

characteristics of core reduction strategies were converted into geometric variables that

can be captured in 3D analysis. Expert flintknappers then created assemblages following

different core reduction strategies. The resulting experimental assemblages were

converted into 3D models and their geometric attributes measured. Given a core

produced with known reduction strategy, it was then determined which variables could successfully predict core reduction strategy. The Levallois and discoidal reduction

strategies were tested with this approach, due to their abundance in MSA assemblages.

This research demonstrated that variables associated with core reduction, including the

ratio between the volumes of two hemispheres, and the ratio of angles between flaking

planes, can successfully differentiate Levallois from discoidal reduction.

The final phase of this dissertation applied the proxies discovered in phase one

and the methods developed in phase two to the MSA archaeological record. The study

xv sites included Nasera, Kisese II, Koobi Fora, Lukenya Hill, Muguruk, and Prospect Farm.

The broader comparative analyses demonstrated that raw material constraints may have

been the primary driver of regional technological patterns. This study also focused on two

individual sites, Nasera and Koobi Fora. Nasera was analyzed across the Middle to Late

Stone Age transition to test the validity of three models of technological change. Koobi

Fora was analyzed across space to examine how different site formation processes affect

perceived patterns of cultural transmission across the landscape. At Nasera, results lend support to the environmental and demographic models. However, the analyses reveal that previously defined industrial designations do not align with new chronologies. At Koobi

Fora, it was demonstrated that geomorphological processes have played a large role on the taphonomic preservation of MSA sites. However, when these processes are controlled for, as at GaJj17, results indicate that raw material was not the sole driver of technological variability, as similar technologies were created on different raw materials.

This dissertation lays the foundation in understanding technological variability in the

MSA based on middle-range theory. Further work is needed at all MSA sites in Eastern

Africa in order to develop a higher-resolution chronological framework and to continue testing models of human behavioral change throughout the Late Pleistocene.

xvi Table of Contents

Dedication ...... iv

Acknowledgements ...... v

Abstract of Dissertation ...... xiv

List of Figures ...... xix

List of Tables ...... xxiii

List of Symbols and Abbreviations...... xxvi

List of Glossary Terms...... xxviii

Chapter 1. Introduction ...... 1

Chapter 2. Investigating empirical traces of cultural transmission in lithic technology with experimental flintknapping ...... 14

Chapter 3. Measurement Protocols and Three Dimensional Methods: Evaluating Core Reduction Strategy with Photogrammetry ...... 54

Chapter 4. Re-thinking Regional Identity in the Middle Stone Age with Behavioral Approaches to Cultural Transmission (BACT) ...... 83

Chapter 5. Nasera Rock and the Middle to Late Stone Age Transition ...... 101

Chapter 6. Late Pleistocene Cultural Transmission at East Turkana: Taphonomic and Site Formation Perspectives ...... 140

Chapter 7. Conclusions ...... 157

References ...... 168

xvii Appendix A. Levallois Reduction Models...... 193

Appendix B. Additional Study Localities ...... 210

Appendix C. Lithic Analysis Definitions...... 243

xviii List of Figures

Figure 1-1. Study localities mentioned in the text...... 13

Figure 2-1. An assistant experimenter (Robert Kaplan) helps collect sequence number as flakes are removed by the flintknapping participant while the author records video and observational notes...... 22

Figure 2-2. 3D model that knappers viewed for emulation task. Provided by University of Minnesota Evolutionary Anthropology Lab...... 25

Figure 2-3. Screenshot of video that knappers watched for the imitation task...... 26

Figure 2-4. Technological Flake Category as defined by Toth (1987)...... 30

Figure 2-5. Platform morphology as measured by platform depth/platform width...... 31

Figure 2-6. Stages of reduction intensity as calculated using observed relative sequence number...... 32

Figure 2-7. Basalt only. The coefficient of variation (CV) for maximum length (red solid line), maximum thickness (green dotted line), platform thickness (blue), and standard deviation of thickness (thickness evenness, purple)...... 35

Figure 2-8. Porcelain only. The coefficient of variation (CV) for maximum length (red solid line), maximum thickness (green dotted line), platform thickness (blue), and standard deviation of thickness (thickness evenness, purple)...... 36

Figure 2-9. Number of direction changes for each condition for the basalt trial...... 38

Figure 2-10. Number of direction changes for each condition for the porcelain trial...... 39

Figure 2-11. Cortex presence+location (technological flake category; Toth 1985) for each condition for the basalt trial...... 40

Figure 2-12. Cortex presence+location (technological flake category; Toth 1985) for each condition for the basalt trial...... 41

Figure 2-13. Platform morphology for each condition for the basalt trial...... 42

Figure 2-14. Platform morphology for each condition for the porcelain trial...... 43

Figure 2-15. Thickness evenness for each condition for the basalt trial...... 44

xix Figure 2-16. Thickness evenness for each condition for the basalt trial...... 44

Figure 3-1. A-D) Volumetric conception adapted from Boëda (1995, 1993). E) Plane extraction method: evenly spaced landmarks are placed along the flaking ridge and the plane is defined as the least squares distance to the landmarks. F) Volume measurement is computed as a scale-free variable above and below the plane of intersection. G-H) Flaking angles of individual flake scars are measured as the angle between the plane of intersection and the plane of the flake scar...... 58

Figure 3-2. A) Upper to lower volume ratios for experimental assemblages, p = 0.058, Mann-Whitney U=12. B) Upper to lower angle ratio (ULAR) for experimental assemblages, p < 0.01, Mann Whitney U=4. C) Upper Angle averages for experimental assemblages. p < 0.01 2, Mann-Whitney U=2.00 D) Primary flake angle of experimental assemblages, p < 0.01, Mann Whitney U=3)...... 67

Figure 3-3. A) Upper to lower volume ratios for Skhul relative to experimental ranges. B) Upper:Lower Angle Ratio (ULAR) of Skhul relative to experimental ranges. C) Upper angle average of Skhul relative to experimental assemblages. D) Primary flaking angle of Skhul relative to archaeological assemblages...... 69

Figure 3-4. Experimental and Skhūl ranges. The yellow star highlights a single core from Skhūl for each of the four variables...... 74

Figure 3-5. Discriminant function analysis of ULVR, ULAR, PFA, and UAA for experimental discoidal (blue), experimental Levallois (orange), and archaeological cores (black). Accurate prediction of experimental discoid, experimental Levallois and archaeological was 76%. All Skhūl cores were assigned to experimental Levallois...... 76

Figure 4-1. Levels of analysis in research on technological organization (Nelson 1991:95) ...... 93

Figure 5-1. Plan view of Nasera Rock showing Leakey (dotted line) and Mehlman (solid line) excavations. From Mehlman 1989...... 111

Figure 5-2. Nasera stratigraphic profile (from Mehlman 1989)...... 112

Figure 5-3 Grid plan of Mehlman’s excavations. From Mehlman 1989 and (Mehlman, 1977)...... 113

Figure 5-4. The Nasera collection upon arrival (left) and after curation (right)...... 116

Figure 5-5. Examples of deteriorating state of Nasera assemblage...... 117

xx Figure 5-6. Missing tools in the Nasera assemblage. Mehlman reported 92 total points in the Nasera assemblage but only a few are still housed in the Leakey Camp collection...... 118

Figure 5-7. Raw material composition through time (from Mehlman 1989)...... 121

Figure 5-8. Core orientation through time at Nasera (from Mehlman 1989)...... 122

Figure 5-9. Core orientation through time at Nasera...... 124

Figure 6-1. Stratigraphic correlation of upper Chari Member (Koobi Fora Formation), showing correlation of sediments above the Silbo Tuff and below the Galana Boi formation (Mavuso et al, In Prep)...... 147

Figure 6-2. Study localities at East Turkana...... 148

Figure 6-3. Koobi Fora Raw Material Diversity...... 150

Figure 6-4. Koobi Fora Reduction Intensity...... 151

Figure 6-5. Core orientation at East Turkana...... 154

Figure A-1. Idealized reduction sequence...... 193

Figure A-2. Technological Flake Category as defined by Toth (1987)...... 195

Figure A-3. Bifacial reduction multiple linear regression observed sequence number versus predicted sequence number...... 203

Figure A-4. Levallois multiple linear regression observed sequence number versus predicted sequence number...... 204

Figure A-5. Pooled prediction model...... 205

Figure A-6. Technological Flake Category versus square root of relative sequence number...... 206

Figure B-1. Study localities described in the text...... 213

Figure B-2. Muguruk stratigraphy from McBrearty (1988)...... 214

Figure B-3. Reduction Intensity Distribution of Muguruk Assemblage ...... 217

Figure B-4. Muguruk elongation index binned into tertiles...... 218

Figure B-5. Map of Prospect Farm from Anthony (1978)...... 220

xxi Figure B-6. Core reduction strategies reported by Anthony (1978) from oldest to youngest layers...... 221

Figure B-7. Sketch of ‘total surface core’ reduction pattern described by Anthony (1978)...... 222

Figure B-8. Kisese II Lithic Sequence (from Inskeep archives, scanned by Jason Lewis)...... 227

Figure B-9. Pieces described in the text as ‘sinew frayers’...... 232

Figure B-10. Idealized section of GvJm16 from Merrick 1975...... 237

Figure B-11. Stratigraphic section of the northern wall of GvJm16, from Merrick (1975)...... 238

Figure B-12. Raw material composition of GvJm16 Industy A reported by Merrick 1975...... 239

Figure B-13. Core orientations by raw material at GvJm16A as reported by Merrick 1975...... 241

Figure B-14. Core orientations of GvJm16A with “amorphous” and “other” raw material omitted...... 241

xxii List of Tables

Table 2-1. Experimental Design of Study...... 21

Table 2-2. Design of Experimental Conditions...... 23

Table 2-3. Coding system of complexity of flake scar directionality. P = proximal, L = left, R = right, D = distal...... 29

Table 2-4. Technological Flake Categories described by Toth (1987)...... 29

Table 2-5 Combined lithic data from both groups...... 33

Table 2-6. Mann Whitney U test results for comparisons between basalt and porcelain for all measurements included in analysis...... 34

Table 2-7. Differences of core reduction strategy variables between baseline, emulation and imitation conditions...... 38

Table 2-8. Differences of flake morphology variables between baseline, emulation, and imitation conditions...... 41

Table 2-9. Survey data of self-reported number of years knapping, number of hours per week knapping, how the participant learned to knap, their experience studying archaeological materials, and familiarity with the tested reduction strategy...... 52

Table 2-10. Amounts of time that knappers spent in each session (in minutes)...... 52

Table 2-11. Mass, density, and Young’s Modulus for porcelain cores. Slight differences were observed between the British and domestic clays. Both clays were fired to Cone 10 (1285-1305°C)...... 53

Table 3-1. Perpere’s 1986 inter-analyst study in which lithicists were asked to assigned the same assemblage into categories based on presence or absence of Levallois technology. Numbers represent the percent of assemblage composition...... 56

Table 3-2. Characters measured in this study and expectations using Boëda’s volumetric conception...... 59

Table 3-3. Inter-analyst reliability tests (n=10)...... 64

Table 5-1. Mehlman radiocarbon results (adapted from Mehlman 1989:45)...... 107

Table 5-2. Mehlman uranium series data (adapted from Mehlman 1989:46)...... 108

xxiii Table 5-3. Amino acid racemization results from fossil bone (Mehlman 1989:46)...... 108

Table 5-4. Nasera amino acid ephimerization results from Kokis (2008)...... 108

Table 5-5. New radiocarbon dates by Tryon and Ranhorn (unpublished)...... 109

Table 5-6. Stratigraphic units used in Nasera BACT analysis...... 114

Table 5-7. Nasera Measured Lithic Dataset...... 118

Table 5-8. Differences in blank production at Nasera through time focusing on Domain 1: Core Modification...... 123

Table 5-9. Platform maintenance at Nasera...... 124

Table 5-10. Platform thickness at Nasera...... 125

Table 5-11. Nasera direction of core exploitation...... 127

Table 5-12. Nasera dorsal surface convexity...... 128

Table 5-13. Toolkit morphology differences at Nasera...... 130

Table 5-14. Differences in Blank Production at Nasera through time...... 131

Table 6-1. Koobi Fora Measured Lithic Dataset...... 149

Table 6-2. Platform thickness descriptive statistics...... 152

Table 6-3. Pair-wise Mann Whitney of platform thickness...... 152

Table 6-4. EPA descriptive statistics...... 152

Table 6-5. EPA pair-wise Mann Whitney results...... 153

Table 6-6. Length/Width ratio at East Turkana...... 153

Table 6-7. Mann-Whitney pair-wise tests for length/width ratio at East Turkana...... 153

Table A-1. Technological Flake Categories described by Toth (1987)...... 194

Table A-2. Complete flakes (including preferential Levallois flakes) measured in the reduction experiment...... 198

Table A-3. Variables measured in reduction experiment...... 198

xxiv Table A-4. Cortex scores...... 199

Table A-5. Correlation coefficients at the level of reduction strategy...... 201

Table A-6. Correlation coefficients at the level of individual reduction sets 10 and 11...... 201

Table A-7. Bifacial reduction linear model with all variables...... 203

Table A-8. Bifacial reduction multiple linear regression when only significant values used...... 204

Table A-9. Levallois multiple linear regression...... 204

Table A-10. Multiple linear regression for pooled data...... 205

Table A-11. Correlation coefficients at the level of individual reduction sets...... 209

Table B-1. Prospect Farm Measured Lithic Dataset ...... 224

Table B-2. Inskeep’s Typology...... 226

Table B-3. Inventory of Kisese lithics present in the NMT...... 235

Table B-4. Measured lithic dataset from GvJm16A (Lukenya Hill)...... 238

Table B-5. Raw material composition of GvJm16 Industry A reported by Merrick 1975...... 238

Table B-6. Bins used to compare Mehlman and Merrick’s core orientations...... 240

xxv List of Symbols and Abbreviations

BACT: Behavioral Approach to Cultural Transmission

BE: Behavioral Ecology

BP: Before Present

CASHP: Center for the Advanced Study of Human Paleobiology

CCS: Cryptocrystalline Silica

CT: Cultural Transmission

CV: Coefficient of Variation

DF: Degrees of Freedom

DRC: Democratic Republic of Congo

EPA: External Platform Angle

EWT: East West Trench

ER: East Rudolph

ESR: Electron Spin Resonance

CE: Central Excavation

GWU: George Washington University

HP: Howieson’s Poort

IGERT: Integrative Graduate Education and Research Traineeship

IRB: Institutional Review Board

ISGS: Illinois State Geological Survey

KA: Thousand Years Ago

KFFS: Koobi Fora Field School

KNM: Kenya National Museum

xxvi LSA: Late Stone Age

MA: Millions Years Ago

MIS: Marine Isotope Stage

MRP: Miscellaneous Retouched Pieces

MSA: Middle Stone Age

NA: Not Applicable

NASTIES: Named Stone Tool Industries

NMT: National Museums of Tanzania

NSC: Normalized Scar Count

NSF: National Science Foundation

NST: North South Trench

OES: Ostrich Eggshell

OSL: Optically Stimulated Luminescence

PFA: Primary Flake Angle

PN: Pastoral Neolithic

PT: Platform Thickness

RMU: Raw Material Unit

SB: Still Bay

TL: Thermoluminescence

UAA: Upper Angle Average

ULAR: Upper to Lower Angle Ratio

ULVR: Upper to Lower Volume Ratio

XRF: X-Ray Fluorescence

xxvii List of Glossary Terms

Bipolar Core: A flaked piece which shows evidence for being knapped using bipolar

technique, i.e. placed on an anvil and struck with a hammerstone such that

resulting force travels through the core to remove a flake. Evidence includes distal

crushing Not to be confused with bipolar flaking as a flaking pattern from

opposite directions, here referred to as bidirectional

Chaîne Opératoire: (French) Operational sequence; the process of stone tool manufacture

beginning with raw material acquisition and ending with tool discard (Bar‐Yosef

and Van Peer, 2009)

Cone: In ceramics, a measure of heat-work. Also used to describe, referring to the

amount of heat-work needed to vitrify (e.g. Cone 6 or Cone 10 clay)

Cultural Transmission: the transmission from one generation to the next, via teaching and

imitation, of knowledge, values, and other factors that influence behavior (Boyd

and Richerson, 1985: 2)

Debitage: Used here to refer to the flaking debris that results from flintknapping.

Emulation: In this study, emulation refers to the process of copying another person’s

result; also referred to as ‘end-state demonstration’. Within social learning

literature, however, definitions of emulation vary.

Imitation: In this study, imitation refers to the process of copying another individual’s

actions; also referred to as ‘technique demonstration’.

Platform Core: A flaked piece in which the striking platform forms close to a 90° angle

with the face(s) bearing the major flake negative scars. (Mehlman 1989).

xxviii Reduction Stage: In this study, reduction stage is used to break down the knapping

process into equal bins, usually “early”, “middle”, and “late”, according to its

place in the sequence of removal of flakes

Raw Material Unit: A class of artifacts based on similarities in macroscopic attributes including texture, color, luster, and fracture mechanics, conceptualized as a knapping episode (Conard and Adler, 1997; Frahm, et al., 2016).

Sequence Number: The number that defines the order in which a flake was removed from a core, i.e. the nth removal.

Social Learning: Ways that individuals learn from other individuals through observation, and modify their behavior.

xxix Chapter 1. Introduction

Humans exhibit extraordinary cultural diversity. Speaking over 6,500 languages

(Anderson, 2012) and practicing different food acquisition systems—from foraging to

pastoralism to agriculture—humans inhabit every corner of Earth from equatorial

savannah to the Arctic Circle to tropical rain forests. In terms of biomass, humans are

among the most biologically successful terrestrial vertebrate on the planet (Smil, 2002).

Decades of research from both hunter-gatherer and non-human primate models suggest that humankind’s extraordinary biological success—and human uniqueness—is derived from an extreme reliance on cultural transmission and cooperation with non-kin (Boyd, et al., 2011; Hill, et al., 2009).

Cultural transmission enabled a suite of cooperative behaviors including food- sharing, allo-maternal care, cooperative food acquisition, and provisioning of goods

(Boyd, et al., 2011; Hill, et al., 2011). When practiced with high-fidelity, that is, successfully encoding, replicating, and thereby preserving observed behavioral patterns, over generations (Tomasello, et al., 1993), cultural transmission produces cumulative culture (Lewis and Laland, 2012), a uniquely derived trait separating humans from other primates (but see Caldwell and Millen, 2009; Dean, et al., 2012; Tennie, et al., 2009).

The origin of high-fidelity cultural transmission represented a critical development in human evolution. Today cultural transmission can be seen in the nose pendant of a young girl in lowland Amazonia, signaling cooperation with a different language group (Hill, et al., 2009), and the narrative da’aangw of consummate singer Mzee Bu’ú Saqwaré of the

Babati-Irangi Hills in Tanzania, recalling litanies of long-dead cultural figures from the

Gorwaa collective past. While observing cultural transmission in living humans is

1 relatively straightforward, based on tangible and intangible heritage documentation,

detecting cultural transmission in the past provides a new challenge.

Archaeologists are limited only to the tangible aspects of heritage. These include

signatures of personal adornment, such as jewelry, ochreous body paint, feathers, and

clothing, as well as cultural alteration of the skeleton, such as skull modification or tooth

avulsion, and finally, landscape modification and use, such as rock art, postholes,

middens, or structures. The earliest purported evidence of jewelry is found in the form of

perforated Nassarius gibbosulus shells which may be as old as ~105 ka at Skhūl

(Vanhaeren, et al., 2006) and ~80 ka at Taforalt (Bouzouggar, et al., 2007), and

perforated Nassarius kraussianus were found in South Africa, dated 75.6 ± 3.4 ka

(Henshilwood, et al., 2004). Engraved ochre from Blombos (Henshilwood, et al., 2009) and ochre processing at Blombos (Henshilwood, et al., 2011) strongly suggests pigment use for art and for bodily adornment by 100 ka, and as early as 164 ka at Pinnacle Point

(Marean, et al., 2007). Clothing and headgear are depicted on Gravettian Venus figurines

29-20 ka (Soffer, et al., 2000). The presence of personal adornment signatures in the archaeological record strongly indicates social networking and high-fidelity cultural

transmission, perhaps as early as 75 ka, and also factors largely into the debate on the

emergence of modern human behavior, particularly symbolism (McBrearty and Brooks,

2000).

When viewed in the broader light of Paleolithic archaeology, beads and ochre

constitute a relatively small percentage of the archaeological record. If cultural

transmission was indeed at work by 75 ka, it should also be observable in other more

ubiquitous archaeological signatures. Stone tools represent another aspect of early human

2 technology, and the most abundant byproduct of past human behavior prior to the

manufacture of pottery. The intentional flaking of stone to produce a durable cutting edge

for scraping, cutting, or other functional purposes is a uniquely defined trait of the

hominin lineage, extending as far back as 3.4Ma (Harmand, et al., 2015). Importantly, the

production of stone tools involves multiple contingent decisions—each requiring tactical

knowledge and spatial comprehension—and is a technology that required learning

(Lycett, et al., 2016). Stone artifacts, therefore, provide a conspicuous mechanism for

investigating cultural transmission in the past.

The archaeological record of eastern Africa is important in the study of

Pleistocene cultural transmission for several reasons. First a central tenet of biology states that molecular distance and divergence time are highly correlated, that is, that divergent populations are more “ancient” than homogenous ones (Wayne, et al., 1991). Multiple lines of evidence point to eastern Africa as the home of the most robust genetic and linguistic diversity today (Tishkoff, et al., 2009) although the causal mechanism of this diversity is not yet understood. Secondly, eastern Africa is home to some of the earliest modern human fossils, from the Omo region, Ethiopia, dating to 195 ka (McDougall, et al., 2005). Human diversity beyond that seen today persisted well into the later

Pleistocene as evidenced at Lukenya Hill (Crevecoeur, et al., 2016; Tryon, et al., 2015a).

When Africa as a whole is considered, regional patterns of hominin toolkits appear to be widespread (Clark, 1988; McBrearty and Brooks, 2000). Standardizations in lithic technology has been especially well-studied in southern Africa (Mackay, et al.,

2014), exemplified by including Howieson’s Poort backed microliths and Stillbay bifacial points. These suites of behavior appear to be limited in space and time (Wurz,

3 2013) but the underlying impetus of this differentiated patterning is unclear. While

considerable interest and effort has been paid to understanding the timing, pattern, and

causes surrounding the Howieson’s Poort and Still Bay industries of South Africa, less

attention has been paid to analogous patterns found in eastern Africa (Mehlman, 1989).

Surmounting evidence suggests not only a similar succession of technologies in eastern

Africa, but also one that is more diverse (Mehlman, 1989).

Clark (1971) developed an evolutionary model arguing that the progressive

increase in toolkit diversity and regional differentiation observed during the Late

Pleistocene represented increasing selective adaptation to specialized environments. He

argued that this process was initiated in the Acheulean (Shipton, 2010) and culminated in

the highly diverse industries of the Late Stone Age (Ambrose, 1998; Clark, 1971;

Deacon, 1972). Glynn Isaac, studying stone artifacts across space at Olorgesailie wrote,

“I find the clear pattern of idiosyncrasy (in subtle tool morphology) for so many of the

sites extremely provocative… and may indicate a cultural transmission system” (Isaac,

1977: 211). In summary, Paleolithic archaeologists have relied heavily on artifact-up

approaches: observing patterns in the archaeological record and subsequently suggesting causal mechanisms, be they environmental (Clark, 1971) or cultural (Isaac, 1977).

Testing the validity of these proposed causal mechanisms, however, requires a deductive approach. A basic understanding of paleoenvironmental variance, combined with experimentally verified methods for studying lithic technology and how it relates to information transfer, is necessary. Knowledge of Late Pleistocene environmental reconstruction has progressed considerably in the last ten years (Blome, et al., 2012;

Faith, 2014; Karkanas and Goldberg, 2010; Tryon, et al., 2014). Despite advances in

4 lithic analysis (Scerri, et al., 2014b; Tostevin, 2012), however, a standardized empirical method for assessing information transfer, especially from MSA toolkits of eastern

Africa, is currently lacking. The first phase of this dissertation (Chapter 2) attempts to

rectify this, guided by hypothesis 1: Differential degrees of information transfer are

detectable in measurable signatures in lithic assemblages. This hypothesis was tested

with social learning flintknapping experiments on standardized porcelain nodules, an

undertaking which required significant method development, refinement, and creativity.

As Chapter 2 details, the study of archaeological lithic assemblages, which are inherently

palimpsests of behavior, as a tool for understanding cultural transmission is still

developing, with Tostevin (2012) pioneering much of the current work. By standardizing

factors known to contribute to lithic variability, such as shape and size of the initial

nodule, and by teaching knappers to create tools under different levels of fidelity of

information transfer, inferential models can be made in which artifacts derived from

known degree of fidelity transmission are directly measured for empirical traces of

information transfer. If the hypothesis is false, and cultural transmission is not detectable

in lithic assemblages, then it is expected that variability of measured characters will not

correlate to degree of transfer fidelity. It becomes important, then, to prevent false

positives—to ensure that any trait that co-varies with degree of information transfer does

so in a manner that cannot be explained by any other phenomenon, be it technological or

mechanistic. If validated, such experimentally verified lithic signatures of high-fidelity

cultural transmission would not only provide new avenues for cognitive scientists to

study social learning in the present, it would also provide archaeologists a referential

framework to study the transmission of ideas in the past.

5 The next phase of this dissertation investigates and creates methods to measure and capture variation in these lithic signatures. As detailed in Chapter 3, there is a large disconnect among Paleolithic archaeologists regarding the manners in which lithic variability is discussed. One of the most common approaches in studying stone tools is the typological approach, in which archaeologists assign stone artifacts to categories based on form. Types, which developed out of potentially real similarities and differences in ancient toolkits, lack repeatability in application which is necessary for international scholarly discourse, and obscure trends of variation (Dibble, 1987). Current debates demonstrate how the already noisy archaeological record may be even further muddied by these semantics (Monnier and Missal, 2014; Shea, 2014). In order to deduce broader phenomena about ancient tool use over time and space, archaeological observations need to be repeatable and falsifiable. This dissertation postulates that studies of variation in stone artifacts are most informative when 1) the lithic measurements are derived ranges of data, which themselves can be repeatedly measured by multiple analysts, rather than, dualistic presence/absence attributes or types and 2) the lithic measurements are tied to technological decisions rather than end form. Giving attention to developing methods in three-dimensional techniques, and drawing largely from morphometric and multivariate approaches used in paleontological studies of morphological variation, the research detailed in Chapter 3 tests the following hypothesis: Previously qualitatively-defined technological categories (e.g. types) can be quantitatively defined with continuous variables using 3D studies that focus specifically on features of stone artifacts that are known to be sensitive to specific technological patterns.

6 Beyond merely quantifying variation in form, this chapter seeks to quantify technological process. Refitting and experimental replication studies which elucidate the chaîne opératoire, or chain of operations, that ancient toolmakers employed in stone tool production (see Soressi and Geneste, 2011), are used to tailor lithic analysis to technologically relevant attributes. Specific focus is given to the Levallois reduction strategy (Boëda, 1995), because Levallois technology likely required social learning and cultural transmission (Lycett, et al., 2016; Mithen, 1997) and is a hallmark of eastern

African later Pleistocene assemblages (see Tryon, et al., 2005). Pinpointing Levallois technology in the archaeological record, however, has proved troublesome, with both

“Levallois cores” and “Levallois flakes” subject to the typological dilemma (Dibble,

1995; Perpère, 1986). To rectify this, Chapter 3 outlines the known technological processes utilized in the Levallois reduction strategy (Boëda, 1995) and converts them to geometric expectations that are measureable in 3D. By re-constructing Levallois technological processes and subsequently measuring variation of the byproducts— focused on traits sensitive to technological decisions—the analyst can translate stone tool production processes from being largely theoretical to observable, and archaeologists can thus compare ancient toolkits in a way that leads to falsifiable and repeatable observations. If the hypothesis above is false, and if types cannot be quantified using observable technological criteria, then it is expected that the technological variables derived from refitting and experimental replication studies would not successfully differentiate types, and instead would results in homogenous undifferentiated variation.

As detailed in Chapter 3, results are presented here that support the hypothesis, providing methods which enable lithicists to study aspects of prepared core reduction

7 strategies with photogrammetry that correlate to previous technological theories. These measurement methods outlined in Chapter 3 can be used to capture the variation of variables associated with transfer of information (as evidenced by the social learning flintknapping experiments detailed in Chapter 2).

In addition to the 3D Levallois study, Appendix A details methods for maintaining analytical control of reduction intensity—a phenomenon known to contribute variation in lithic assemblages (Braun, et al., 2008; Toth, 1987)—by measuring variation in technological variables across the reduction sequence of experimentally reproduced prepared core reduction schemes. This phase of the research was a prerequisite to the comparative lithic analyses, because in order to study core reduction strategies across the sequence, it is necessary to bin assemblages according to stage in the reduction, be it early, middle, or late. However, many of the variables currently used to bin assemblages

(e.g. Toth’s technological flake category (1987)) are based on experiments that used

Early Stone Age technological methods. It is not clear how prepared core methods affect these variables, and whether or not they can accurately predict relative sequence number of a flake. To investigate this, cobbles were reduced using two core reduction strategies

(Levallois method according to Boëda (1995), and bifacial reduction leading to production of handaxess). Following methods laid out in Braun et al (2008), the sequence number of each flake was recorded upon removal, and subsequent analysis tested which, if any, lithic attributes were good predictors of sequence number. In sum, the 3D methods laid out in Chapter 3, coupled with the reduction experiments in Appendix A, can be applied to lithic assemblages to study core reduction strategies, which according to

8 results in Chapter 2, represent the clearest signal of complex learned technological

processes.

The next phase of this dissertation involved systematic study of Paleolithic

assemblages from eastern Africa. Testing models of cultural transmission requires

detailed analyses of assemblages derived from known contexts, with high-resolution

chronological information and paleoenvironmental data. After considerations regarding

assemblage integrity, six sites were chosen for study, all of which are currently housed in

Tanzania and Kenya: Koobi Fora, Muguruk, Prospect Farm, Nasera, Lukenya Hill, and

Kisese II. Each assemblage was studied quantitatively and qualitatively in order to

confirm and/or critique previous descriptions of the assemblages, and to assess the

overall integrity of the assemblage.

Chapter 4 reviews the scholarly discourse regarding cultural transmission in

Paleolithic assemblages. Drawing heavily from Tostevin’s Behavioral Approach to

Cultural Transmission (BACT), this chapter reviews the theoretical underpinnings that guide this research, including Carr’s Unified Middle-Range Theory of Artifact Design, the chaîne opératoire school, Behavioral Archaeology, and Technological Organization

(TO). Building on this, Chapter 4 lays out two MSA research problems that are

investigated with the BACT approach, outlined in the subsequent chapters.

The first question is described in Chapter 5 and includes the Middle to Late Stone

Age transition at Nasera. The second question, described in Chapter 6, discusses cultural transmission across landscapes at East Turkana. As such, Appendix B describes necessary background information regarding site history, stratigraphy, and curation

9 history. Results of each analysis are also discussed for each individual site in Appendix

This final phase of the dissertation does not benefit from the experimental control of the previous phases, and, as with any archaeological analysis, noise is inherent. The goal of this final phase was not to limit this noise, but rather to use the methods gleaned from the experiments of previous chapters to determine if the patterns within the noise were the result of cultural transmission or functional constraints. If the hypothesis is

false, and if Eastern African toolkits do not demonstrate signatures of information

transfer, then a strong argument can be made in support of J.D. Clark’s hypothesis that

early modern human populations were fragmented by ecological niches, and

differentiated toolkits represent increasing adaptation to specialized environments. This

would have implications for understanding early modern human demographics and

fragmentation, and debates regarding ancient human behavioral responses to climate

variability.

Support for this hypothesis would suggest that early modern humans in the Late

Pleistocene engaged in high-fidelity cultural transmission of stone artifact production

technology, potentially expanding beyond their home bases and connecting with non-kin.

These results could be viewed in tandem with other forms of lithic evidence of social

networks, such as the long-distance movement of obsidian (Blegen, 2017) by 200 ka, and

the nucleation of raw material procurement, such as that seen by the Holocene in

Savannah Pastoral Neolithic and Elementeitan assemblages (Goldstein and Munyiri,

2017), as well as other forms of social adornment evidence like eggshell beads (Ambrose,

10 1998) and ochre (Henshilwood, et al., 2009). In short, positive support for the hypothesis would not be entirely surprising.

Finally, alternative scenarios must be considered. A false negative is possible in the event that no evidence of cultural transmission is found, the absence of which is due to the signatures being undetectable in the observed dataset, for example, due to raw material constraints. Given that a large portion of the dataset is comprised of quartz, which is harder to interpret due to a lack of experimental references, this scenario cannot be ignored. A false positive is also possible, in which signatures of cultural transmission are observed, but are the result of equifinality or homology, in which similarities in technologies are merely the result of multiple, independent inventions. The social learning experiments presented in Chapter 2 help to rectify this phenomenon, and suggest that core reduction strategies are less susceptible to this phenomenon.

A most likely scenario is that both processes—functional considerations and the transfer of cultural information—were at work in the Late Pleistocene of eastern Africa.

This scenario would be exemplified by a pattern in which technological strategies were constrained to certain kinds of environments, but transcended geographic space, such as the spread of technology across a savanna woodland refugium in both southern Kenya and north-central Tanzania. Such evidence would have implications for hypotheses regarding spatial patterning of resources (Yellen, 1977) and its effects on social behaviors like territoriality (Marean, 2016). This could possibly suggest that resource distribution influenced social behavior not by making humans more territorial, but more prosocial and cooperative. The significance of this dissertation, therefore, lies in the methods it develops, the new synthesis of technological change it provides for the Late Pleistocene

11 of eastern Africa, and also its contribution to model-building for future research on early modern human social behavior.

Figure 1-1. Study localities mentioned in the text.

Chapter 2. Investigating empirical traces of cultural transmission in lithic technology with experimental flintknapping

2.1 Previous Experimental Work on Social Learning and Paleolithic Assemblages

The past three decades have seen a steady increase in research regarding cultural

evolution within an evolutionary framework, particularly with cultural transmission

theory. Lithic approaches that specifically examine cultural transmission increased

following the development of dual-inheritance theory which formalized cultural

transmission (CT) as an evolutionary mechanism (Boyd and Richerson, 1985). This was

followed by a growing interest in the role of cultural transmission in cultural evolution. A vast majority of CT studies focused on the processes and constraints that guide human

CT (Boyd and Richerson; Shennan 2000; Henrich and McElreath; Lyman and O’Brien

2003). CT studies that specifically sought to understand archaeological patterns and human evolutionary history have been less common, and are summarized here.

Eerkens and Lipo (2005) used modeling to simulate how copy errors can be transmitted and amplified over time, given different forms of transmission direction and bias, generating variation in the archaeological record. For example, Eerkens and Lipo demonstrate that the coefficient of variation (CV) of an artifact trait decreases when conformist transmission is at work, that is, when individuals conform to the average of the previous generation’s value. A surprisingly low value of conformance (5%) was needed to reduce CV by half its original value over time. A similar model was produced under prestige-biased transmission, in which individuals copy traits only from prestigious individuals. Eerkens and Lipo (2005) conclude that most cultural transmission biases will reduce the amount of variation of a particular trait in a population, and that the absence of

14 such biases will lead to a baseline of variation due to copy errors. This conclusion formed a null-model of variation by which assemblages could be studied. If a particular trait, such as projectile point thickness, exhibited a CV that increased over time, Eerkens and

Lipo concluded that no transmission was at work, and that the variation was simply a product of copy errors. However if the CV varies dramatically, as in diameter measurements of Illinois Woodland potsherds, exhibiting high variation followed by sudden standardization, it can be concluded that some form of rule-based transmission was at work during the latter. Eerkens and Lipo’s work importantly provided null models, later called the “accumulating copy error” (ACE) model, against which archaeological observations can be tested. When variation is observed in the archaeological record, they argued, complex explanations should be avoided until all simpler causes have been ruled out. The null model of variation arising from copy errors provides one such approach.

Schillinger et al (2015) sought to test Eerkens and Lipo’s ACE model with actual artifact production experiments. Their goal was to determine how shape, rather than linear measurements such as thickness or width, is affected with accumulating copy errors, particularly within ‘artifactual shape traditions’ like handaxe manufacture.

Moreover, Schillinger et al sought to understand how the reductive nature of tool manufacture affected variation due to copy error accumulation. As such, they asked participants to create ‘handaxess’ out of plasticine foam, under two conditions: 1) additive-reductive, in which participants could both remove and add material, and 2) reductive-only, in which participants could only remove material. Their results demonstrated that the variation in the reductive-only condition was higher than the reductive-additive condition. Therefore, they conclude that shaped artifacts formed with

15 reductive processes are inherently unstable, and will tend toward higher variability in the

absence of any stabilizing mechanism. Furthermore, each reduction event increases the risk of copy error at the next step (Schillinger, et al., 2015).

Studies like Eerkens and Lipo (2005) and Schillinger et al (2015) demonstrate the role of copy errors in producing variation. What is not clear, however, is what happens when those copy errors become embedded in technology as improvements. Tennie et al

(2009) argue that indeed a unique characteristic of human culture is the ability to accumulate modifications over time. Human cultural transmission, they argue, is characterized by ‘the ratchet effect’—the process by which improvements and modifications stay within a generation with little slippage or decrease, and remain relatively stable until they are improved, or ratcheted up, again. In this way, when individuals build on technologies that are taught to them, they are cooperating with those individuals before them who invented the technology. This form of cooperation is unique to humans, and plays an important role in human cultural transmission.

The cooperative nature of human cultural transmission has important implications for human social learning. Social learning, writ large, refers to ways that individuals learn from other individuals through observation, and modify their behavior. Imitation, the process by which an individual copies another individual’s actions, is common across the

Primate Order (Call and Tomasello, 2008; Subiaul, et al., 2004; Whiten, et al., 1999).

However, humans are unique in the ways that they imitate. Human children imitate even when the functional outcome is undesirable, as a means to be social and interact with others (Nielsen, 2009). Kalahari children have been shown to imitate obsolete actions that lead to no outcome (over-imitation) (Nielsen and Tomaselli, 2010). The overt social

16 nature of human learning, sometimes leading to copying of erroneous actions, is likely an

evolutionary adaptation necessary for the transmission of culture (Nielsen and Tomaselli,

2010).

Emulation is another form of observational social learning, and is less studied

than imitation. Emulation refers to the copying of another individual’s intentions or goals,

without necessarily copying their action, although there are several varieties (Subiaul, et al., 2016; Tomasello, 1999). Emulation usually involves the process of an individual learning from their environment in an associative way, for example, observing an end- state, such as an opened box, and determining that the box must be opened in order to reveal what is inside (Carpenter, et al., 2002). The fidelity of copying, or accuracy of replication, is decreased in emulation relative to imitation, because the imitator is not there to directly demonstrate the actions (Tennie, et al., 2009; Whiten, et al., 2009).

Importantly, emulation does not require the observer (learner) and the acting agent

(teacher) to interact directly. In emulation, the process of the learner simply observing the outcome of the acting agent can occur well after the acting agent leaves a location.

These different forms of social learning may have been important in human behavioral evolution, particularly during the MSA when the uniquely human form of cooperative behavior was emerging (Marean, 2016). For example, a forager finding a piece of flaked stone on the ground and deducing that a flake must be struck off a stone in order to be sharp is a form of emulative learning. However, a young child observing their parent flintknapping, and subsequently striking stones together, constitutes imitation.

Missing from the studies discussed so far is any explicit link between measureable stone artifact attributes and fidelity of transmission of information. While much work has

17 modeled cultural transmission on artifact variation across generations, it is not clear if or

how different social learning mechanisms become embedded in tool morphology.

2.2 Objectives of Social Learning Experiments

This phase of research therefore used controlled experimental flintknapping sessions in which the independent variable was degree of fidelity of cultural transmission, and the dependent variable(s) are measured attributes. In other words, given an assemblage in which the fidelity of information transfer is known, how do technological

attributes vary?

A primary objective was to determine if and how imitative cultural transmission

can be differentiated from emulative social learning in lithic assemblages. This study

used Levallois, or prepared core technology, as a testing model, because it represented a

widespread Stone Age technological approach, comprised of several methods, with

limited geometric variability across space (Lycett and von Cramon-Taubadel, 2013). The

Levallois production sequence also has implications for social learning and population

dynamics (Lycett and Norton, 2010; Mithen, 1997) and its spread may have required

teaching (Lycett, et al., 2016; Ranhorn, et al., 2015). If an MSA forager found a Levallois

flake while on a foray, would they be able to copy it without a teacher? If they did, would

these flakes look similar to flakes that were taught by a teacher, or different? These

questions stem largely from the premise that lithic technologies may represent migrations

of paleo-populations e.g. Nubian cores as representative of “out of Africa” migrations

(Rose, et al., 2011), or the Chatelperronian as a signature of interaction with modern human populations (Mellars, 1992). An ever-present problem with these hypotheses is convergence—the possibility that people independently invented these technologies e.g.

18 (Will, et al., 2015). A nuanced but under-discussed alternative hypothesis to the convergence theory involves social learning without interaction—that technologies

spread not because they were independently invented nor were they directly taught, but

rather that they were simply “learned” via emulation (the MSA forager picking up a flake and copying it). If this was the case, it would still constitute a form of social learning and still implies that groups were connected, even if they did not directly interact. This is important because emulation alone can lead to cumulative cultural evolution, in the absence of teaching and imitation, as demonstrated by Caldwell and Millen (2009). Thus the ability to detect emulation in lithic assemblages will have great impact on interpretations of lithic variability across space and through time, particularly models of population migrations and expansions, as well as models of technological innovations.

Currently it is not well understood how lithic products vary when independently invented, copied, or learned because it is currently unclear how lithic traits vary once embedded in cultural transmission chains. Tostevin (2012) developed a novel approach to lithic analysis to accomplish this, distilling lithic tool production into its constituent domains of knapper choices. This work is further discussed in Chapter 4. However,

Tostevin also admits that Paleolithic archaeology lacks an understanding of how these decisions vary across reduction sequences, given that with each removal there are fewer choices available and more constraints on fracture mechanics (Odell and Henry, 1989).

Tostevin also questions if behavioral categories even maintain their independence across the reduction sequence when the knapper must sustain core exploitation (2012:138).

Once archaeologists understand this process in a closed system with no time averaging, these models can be used to understand how time averaging and other factors (e.g. water

19 transport) might affect assemblage composition. The underlying question in this experiment therefore was, what are the empirical effects of emulation and imitation on lithic attributes? Imitation involves directly copying another’s responses to achieve a result (i.e. reproducing specific ways of interacting with an object). In contrast, emulation, as defined here, involves independently inferring the responses necessary to recreate a given result without any demonstration: reverse engineering. In this experiment, imitation is conceptually distinct and dissociable from emulation. In sum, the experiment involved three within-subject conditions: a baseline condition (what the knapper regularly does with no social learning), an emulation condition, and an imitation condition.

It is entirely possible, however, that there are no defining lithic attributes that, when studied together, signal emulation. Instead it is possible that most of the variation in toolkits is related to raw material mechanics and other functional needs. If that is the case, discussions of MSA and LSA technocomplexes (e.g. Howieson’s Poort, Still Bay,

Lupemban) require dramatic revision. If, as often assumed, there is some aspect of cultural information ‘locked up’ in lithic technology (Isaac, 1977: 207), the representation of which is subsequently shaped by raw material and functional constraints, then it should be possible to observe how this information becomes embedded in lithic palimpsests.

2.3 Social Learning Experiment Methods

2.1.1 Participant pool and recruitment

Experienced flint knappers were recruited from flint knapping groups in North

America. IRB approval for this project has been granted (GWU IRB #051431). These

20 knappers met the criteria of being able to do controlled flaking, as defined by the ability to remove a flake outlined in chalk. Digital survey with a questionnaire was conducted using E4 software (McPherron and Dibble, 2003) to ensure that the participants were not previously familiar with the Levallois or prepared core knapping strategies. Survey data also recorded self-reported number of years knapping, number of hours per week knapping, how the participant learned to knap, their experience studying archaeological materials, and familiarity with the tested reduction strategy (Table 2-9). All participants knapped in individual isolated sessions to minimize external information transfer.

Knapping experiments occurred in three sessions and were video recorded to enable future coding of knapping behavior.

Two trials were conducted: basalt trials and porcelain trials. In the basalt trials, knappers used natural Oregon basalt cobbles obtained through Neolithics.com. In the porcelain trials, participants were given a porcelain nodule in which the shape and interior raw material was standardized (Khreisheh, et al., 2013). Prior to the experimental reduction in both trials, all nodules were weighed. Only ellipsoid and rounded hammerstones from GWU campus were used; antler, copper, and other billets were not utilized in the study.

Table 2-1. Experimental Design of Study.

Trial Experimental Conditions A B C 1. Basalt Baseline End-State Technique Demonstration Demonstration 2. Porcelain Baseline End-State Technique Demonstration Demonstration

The sequence of removals for all flakes was recorded. This was achieved by removing each flake as it was removed from the core. In the event that a flake snapped or

21 shattered, all pieces were retrieved and labeled Xa, Xb, Xc, and so on. Sequence number was recorded for all flakes greater than 2cm. The start time and end time for each session was also recorded and general observational notes were taken throughout the sessions.

Figure 2-1. An assistant experimenter (Robert Kaplan) helps collect sequence number as flakes are removed by the flintknapping participant while the author records video and observational notes.

2.1.2 Experiment Description – Baseline, Emulation, and Imitation

Table 2-2 shows the design of each experimental condition used in the study, including a description of the knapping task, and the fidelity of information transfer involved in each. The levels of fidelity of information transfer and their relationship with emulation and imitation are derived from social learning studies (Subiaul, et al., 2015). In the first condition (Baseline) participants were asked, “Produce 5 usable flakes”. No further instruction was given. This condition corresponds with low information transfer and is associated with low-fidelity learning as no demonstration was provided.

22 In the second condition (End-State Demonstration, corresponding with emulation

learning) participants were shown a 3D reconstruction of an artifact of a particular shape

and size (e.g. “Levallois point”). Knappers were told, “Study this 3D model for as long as

you like but for at least one minute. Please create five flakes that look like the 3D

model.” This condition corresponds with mid- to moderate- information transfer and is

associated with mid-fidelity learning as only the end-result (but not the means) was

demonstrated.

In the final condition (Technique Demonstration, corresponding with imitation

learning) participants were shown an instructional video with audio demonstrating step-

by-step preferential Levallois flake production. The participant was asked, “Please

produce 5 flakes that look like the one produced in the video.” This condition

corresponds with high-information transfer and is associated with high fidelity learning

as the goals, means, and end-result of actions was demonstrated.

Table 2-2. Design of Experimental Conditions.

Condition 1 Condition 2 Condition 3 Social Learning Baseline Emulation Imitation Correlate Task Description No demonstration End-state Technique demonstration demonstration Fidelity of Low Medium High Information Transfer

Each knapper was tested in a single trial for all three conditions, in the order described above: Baseline, Emulation, Imitation. There was no time limit to the knapping sessions. Knappers were able to knap as long as they wanted to and to decide themselves when to end (Table 2-10). Some knappers stopped knapping after the task was finished

(e.g. after five flakes were produced) and other knappers continued knapping until the

23 nodule was exhausted. All knappers followed the instructions. In some cases, especially

in the imitation task in which knappers had to re-create a Levallois sequence and remove

a preferential flake, they were not able to produce 5 preferential flakes and opted to stop

knapping when the core was exhausted. This occurred with four participants. Instead, the

participant chose flakes from their debitage pile that most resembled the Levallois flake

produced in the video. An experimenter was present in each knapping session and did not

provide any knapping advice. One knapping participant was discarded from the analysis

because they did not finish all three sessions.

2.1.3 Standardized Porcelain Nodules

Nodules of standardized size and shape were created using porcelain following

(Khreisheh, et al., 2013). The porcelain was Standard #257 English Porcelain (Cone 10)

and Standard #130 Domestic Porcelain (Cone 10) purchased from Clayworks Supplies in

Alexandria, Virginia. A two-piece press mold of Plaster of Paris of a 116 x 93 x 65mm

ellipsoid cobble was created. Using the two-piece press mold, the porcelain clay was shaped into standardized nodules. The nodules dried out over the course of two to three weeks. The nodules were then fired to Cone 10 in an electronic kiln, or 1285-1305°C.

Temperatures were increased incrementally by the hour and then held for three hours at

Cone 10 to ensure even vitrification. Young’s modulus was recorded using pulse-echo

velocity measurement technique on multiple nodules to verify standardization of

elasticity, a proxy for rock flaking mechanics (Table 2-11).

Figure 2-2. 3D model that knappers viewed for emulation task. Provided by University of Minnesota Evolutionary Anthropology Lab.

Figure 2-3. Screenshot of video that knappers watched for the imitation task.

26 2.1.4 Expectations

The objective of this experiment was to determine if different forms of cultural transmission (emulation and imitation) produce measureable signatures in lithic byproducts. Because emulation is associated with low-fidelity information transfer, and imitation is associated with high-fidelity information transfer (Tennie, et al., 2009;

Whiten, et al., 2009), it is expected that for all measured attributes, the lithic byproducts of the imitation condition will exhibit less variation relative to those of the emulation condition. Because the knapper copied a 3D model in the emulation condition, and a video demonstration in the imitation condition—in neither session did the knapper copy a tangible flake—it is not possible to compare the variation of the experimental assemblages relative to the demonstrated flake(s). Instead, the variation of the experimental assemblages as a whole was measured for each condition. As fidelity of information transfer increases, the variation of the flakes produced is expected to decrease. Therefore, the coefficient of variation (CV) is expected to be lowest in the imitation task for all measurements. This expectation was tested with four variables that are commonly measured in Paleolithic assemblages as representations of general flake shape (Eerkens and Lipo, 2005; Scerri, et al., 2014a). These variables were: maximum thickness, maximum length, platform thickness, and thickness evenness. Thickness evenness (Presnyakova, et al., 2015), provides a valuable measurement of shape as it is composed of six thickness measurements distributed across the flake. The evenness of thickness value was calculated by taking the standard deviation of these six measurements for each flake. Lower values of standard deviations of thickness correspond to flakes that are more evenly thick, and vice versa. The CV of maximum

27 thickness, maximum length, platform thickness, and thickness evenness are expected to be

lower in the imitation condition relative to the emulation condition.

The second objective was to determine if any lithic measurements perform better

than others at predicting degree of information transfer. Because flake morphology is

subject to forces of equifinality, such that the two knapping sessions may produce similar

flake morphologies via different trajectories, it is expected that variables associated with

flake morphology will not be strong predictors of fidelity of information transfer and that

there will be no significant differences in flake morphology attributes between the two

experimental conditions. Because knapping is a reductive process with several possible

trajectories, it is expected that attributes that are attuned tothese trajectories—referred here as core reduction strategies—will be better indicators of information transfer, and will thus be significantly different between the emulation and imitation conditions.

Variables measured here that correspond to core reduction strategy are complexity of

flake scar directionality (Tostevin, 2012) and cortex presence+location (Douglass, et al.,

2008; Tostevin, 2012; Toth, 1985). Variables presented here that are associated with

flake morphology are evenness of thickness (Eren and Lycett, 2012; Presnyakova, et al.,

2015) and platform morphology (Dibble, 1997; Magnani, et al., 2014; Tostevin, 2012).

2.1.5 Analytical Methods

Complexity of flake scar directionality was measured using a scored system of

direction changes. Each flake was divided into four vectors: proximal, left, right, and

distal (Van Peer, 1992). Four vectors were used to simplify analysis. A higher number of

vectors (e.g. 6, 8) is sometimes chosen, and this analysis can be further aided with 3D

measurement (Hunstiger, 2016). However since the bulk of flake analysis is done by

28 hand without 3D aid, four vectors was chosen because it only requires the analyst to

visualize a difference of 90 degrees and can easily be done with graph paper. The number

of flake scars originating from each vector was recorded. These counts provided an

objective measure of directionality, and were also used in calculating flake scar

complexity scores. If a flake had no flake scars, it was given a score of 0. If a flake had

only flake scars originating from the proximal sector it received a score of 1. If the flake

had two directions represented it received a score of 2, and so on (see Table 2-3).

Table 2-3. Coding system of complexity of flake scar directionality. P = proximal, L = left, R = right, D = distal.

Flake Scar Score Directionality No scars 0 P 1 PL, PR, or PD 2 PLR or PLD or 3 PRD PLRD 4

Cortex presence+location was measured using the technological flake category

developed by (Toth, 1987) Table 2-4; Figure 2-4). This variable captures both the

presence and location of cortex on a flake and is relatively strong predictor of sequence

number (Braun, et al., 2008; Douglass, et al., 2015).

Table 2-4. Technological Flake Categories described by Toth (1987).

Cortical Platform Non-cortical Platform

Full Dorsal Cortex I IV Partial Dorsal Cortex II V No Dorsal Cortex III VI

Figure 2-4. Technological Flake Category as defined by Toth (1987). Evenness of thickness was measured using six measures of thickness following and (Eren and Lycett, 2012). Thickness measurements were taken at 25%, 50%, and 75% intervals of the maximum axis of the flake, 25% and 75% intervals of the maximum width of the flake, and the maximum thickness was measured. Evenness of thickness was calculated as the standard deviation of these thickness measurements following

(Presnyakova, et al., 2015). More evenly thick flakes will have a standard deviation closer to 0, and flakes that vary in thickness will deviate from 0. Platform morphology was measured as platform thickness (depth) divided by platform width, producing a ratio of platform morphology ranging from “linear” to “square”.

Figure 2-5. Platform morphology as measured by platform depth/platform width.

When possible, analysis was carried out at three levels of inquiry: i) pooled data

ii) binned by individual flintknapper and iii) binned by reduction stage. Sample sizes of

individual reduction sets are too small to also bin by reduction stage. It is suggested here

that the pooled data scale is most relevant to the archaeological record, in which it is

impossible to know the number of knappers that created an assemblage.

Controlling for reduction intensity

Flint knapping is a reductive process. As such, the measured attributes of interest in this study are expected to change across the knapping sequence. Therefore the dataset here was controlled for stage in the reduction sequence. In order to do this, observed relative sequence number was used to bin the assemblage into three equal bins, representative of “Early Stage,” “Middle Stage”, and “Late Stage”. Observed relative sequence number was calculated by dividing the observed sequence number by the total sequence length of each reduction set.

Figure 2-6. Stages of reduction intensity as calculated using observed relative sequence number.

2.4 Social Learning Experiment Results

2.1.6 Porcelain Cores

Young’s modulus of the two clay bodies (Standard #257 and Standard #130) were

roughly similar, ranging from 55-58 E. This value for Young’s modulus is relatively low

compared to industrial grade porcelain tiles which exhibit a Young’s modulus ≥ 60 E at

the same temperature at which these clays were fired (1285-1305°C) (Kurama and Elif,

2012). This difference in elasticity may be due to differential porosity resulting from

slight variations in the clay recipes, e.g. percent composition of kaolinite. The relative

precision across all nodules demonstrates a high degree of standardization in elasticity of

the experimental cobbles.

32 2.1.7 Composition of the Dataset

Thirteen flintknappers participated in the study (10 male, 3 female). Participants were tested in one of two groups: I) basalt (n = 6) and II) standardized porcelain nodules

(n = 7). Together, they produced 39 total reductions and 536 lithic pieces (Table 2-5).

The average amount of time knapping was greatest in the imitation session (25 minutes) and least in the baseline session (5 minutes) (Table 2-10).

Table 2-5 Combined lithic data from both groups.

Lithic Artifact Baseline Emulation Imitation Total Class Core 21 14 12 47 Debitage 94 112 162 368 Flake Product 43 41 37 121 Total 158 167 211 536

Some reductions produced more than one core. This occurred when a knapper

removed a large mass and subsequently removed flakes from it, thus initiating a separate

reduction chain. This also occurred when a core broke and was subsequently flaked. The

analysis was conducted in a way to represent archaeological analysis as much as possible.

Thus, even if the broken pieces could be refitted, they were analyzed as separate cores.

Flake products refer to the products that the knapper ‘chose’. In the Baseline session, these are products the knapper deemed usable. In the Emulation session, flake products are those that the knapper deemed similar to the 3D model. In the Imitation session, flake products are those that the knapper produced after preparing the core (the “Levallois flake”). In many cases (n = 17) the knapper chose less than 5 flake products and in some cases (n = 8) knappers did not choose any flake products. For analysis purposes, Flake

Products were combined with debitage and measured accordingly.

33 2.1.8 Variation of Lithic Byproducts by Raw Material

Participants in the two trials (basalt and porcelain) performed differently based on

maximum thickness, thickness evenness, maximum length, and platform thickness of

lithic byproducts. Therefore all subsequent analyses analyzed the two trials

independently, i.e. compare only similar raw materials.

Table 2-6. Mann Whitney U test results for comparisons between basalt and porcelain for all measurements included in analysis.

p-value U Maximum < 0.001 2647 Thickness Thickness Evenness < 0.001 3524 Maximum Length < 0.001 782 Platform Thickness < 0.001 3638.5 Platform 0.125 4623.5 Morphology Cortex Score 0.175 9591 Adjusted Directions 0.475 8252

2.1.9 Variation of Lithic Byproducts with Fidelity of Information Transfer

The first expectation as described above states that lithic byproducts derived from

imitation will exhibit less variation than those of emulation. This expectation was tested

by calculating the coefficient of variation (CV) of four variables: maximum thickness,

maximum length, platform thickness, and thickness evenness. The results of this analysis

are shown in Figure 2-7 for basalt and Figure 2-8 for porcelain.

For the basalt trials, CV decreased for all variables for both the imitation and

emulation conditions relative to the control group. The CV was lowest in the emulation condition relative to the imitation condition.

For the porcelain trials, all four variables exhibited different trends for CV. Both platform thickness and maximum width exhibited similar CV for emulation relative to baseline, followed by a slight decrease for the imitation condition. Maximum thickness was higher in the emulation condition relative to baseline, and was similar for the imitation condition. Platform thickness was substantially higher in the emulation conditions relative to both other conditions.

36 2.1.10 Lithic Variation in Imitation and Emulation

The next expectation as described above is that variables related to core reduction strategy will be better predictors of fidelity of information transfer than variables associated with flake morphology. This was tested by analyzing the four lithic aspects described above: cortex presence+location and direction complexity as proxies for core reduction, and platform morphology and thickness evenness as proxies for flake morphology.

Core Reduction Strategy Variables

Directionality

Figure 2-9 shows the number of direction changes for each condition for the basalt trial. There is a significant difference among the three groups, according to Kruskal

Wallis rank sum test (p = 0.003; Table 2-7). The imitation condition exhibited the highest number of direction changes and this difference from baseline was significant (p = 0.003;

Table 2-7). The emulation condition showed a non-significant difference from baseline (p

= 0.094; Table 2-7).

Figure 2-10 shows the number of direction changes for each condition for the porcelain trial. These three conditions performed differently according to Kruskal Wallis rank sum test (p = 0.034; Table 2-7). Again, the imitation condition exhibited the highest number of direction changes and this difference from baseline was significant (p = 0.045;

Table 2-7). The emulation condition showed a non-significant difference from baseline (p

= 0.308; Table 2-7).

37 Table 2-7. Differences of core reduction strategy variables between baseline, emulation and imitation conditions.

Variable Trial Pair-Wise Mann Whitney U Kruskal-Wallis (p-values) Baseline Emulation Directionality Basalt Emulation 0.094 - χ2 = 11.34; df = 2 Imitation 0.003 0.094 p = 0.003 Directionality Porcelain Emulation 0.308 - χ2 = 6.753; df = 2 Imitation 0.045 0.308 p = 0.034 Cortex Basalt Emulation 0.069 - χ2 = 7.395; df = 2 Imitation 0.036 0.342 p = 0.025 Cortex Porcelain Emulation 0.002 - χ2 = 15.394; df = 2 Imitation < 0.001 0.895 < 0.001

Figure 2-9. Number of direction changes for each condition for the basalt trial.

Figure 2-10. Number of direction changes for each condition for the porcelain trial.

Cortex

Figure 2-11 shows the cortex variable for each condition for the basalt trial. There is a significant difference among the three groups, according to Kruskal Wallis rank sum test (p = 0.025; Table 2-7). The imitation condition exhibited the highest number of type

5 and 6 flakes, and this difference from baseline was significant (p = 0.036; Table 2-7).

The emulation condition showed a non-significant difference from baseline (p = 0. 069;

Table 2-7).

Figure 2-12 shows the cortex variable for each condition for the porcelain trial.

The three conditions produced different patterns according to Kruskal Wallis W rank sum test (p = 0.025; Table 2-7). Again, the imitation condition exhibited the highest number of direction changes and this difference from baseline was significant (p = 0.045; Table

39 2-7). The emulation condition showed a non-significant difference from baseline (p =

0.308; Table 2-7).

Figure 2-11. Cortex presence+location (technological flake category; Toth 1985) for each condition for the basalt trial.

Figure 2-12. Cortex presence+location (technological flake category; Toth 1985) for each condition for the basalt trial.

Flake Morphology Variables

Table 2-8. Differences of flake morphology variables between baseline, emulation, and imitation conditions.

Variable Trial Pair-Wise Mann Whitney U Kruskal-Wallis (p-values) Baseline Emulation Platform Basalt Emulation 1.000 - χ2 = 1.680; df = 2 Morphology Imitation 1.000 1.000 p = 0.432 Platform Porcelain Emulation 0.890 - χ2 = 0.956; df = 2 Morphology Imitation 0.570 0.890 p = 0.620 Thickness Basalt Emulation 0.699 - χ2 = 4.868; df = 2 Evenness Imitation 0.082 0.047 p = 0.088 Thickness Porcelain Emulation 0.678 - χ2 = 0.273; df = 2 Evenness Imitation 0.915 0.645 p = 0.873

Platform Morphology

Figure 2-13 shows the platform morphology for each condition for the basalt trial.

There were no significant differences among the three groups according to Kruskal

41 Wallis rank sum test (p = 0.432; Table 2-8). There were also no significant differences

between the groups, based on pair-wise Mann Whitney U (Table 2-8). The porcelain trial showed similar results, with no significant differences between or among groups (Figure

2-14; Table 2-8).

Figure 2-13. Platform morphology for each condition for the basalt trial.

Figure 2-14. Platform morphology for each condition for the porcelain trial.

Thickness Evenness

Figure 2-15 shows thickness evenness for each condition for the basalt trial. There were no significant differences among the three groups according to Kruskal Wallis rank sum test (p = 0.088; Table 2-8). The imitation condition resulted in flakes that were more evenly flake dthan those in the emulation condition, and this difference was significant (p

= 0.047; Table 2-8). The porcelain trial showed no significant differences between or among groups for thickness evenness (Figure 2-16; Table 2-8).

Figure 2-15. Thickness evenness for each condition for the basalt trial.

Figure 2-16. Thickness evenness for each condition for the basalt trial.

44 2.5 Social Learning Experiment Discussion

The first expectation of this study stated that as fidelity of information transfer increased, the CV of lithic attributes would decrease. This expectation was tested using four lithic attributes: platform thickness, maximum thickness, thickness evenness, and

maximum length. For the basalt trial, this expectation was confirmed. All four variables

showed a marked decrease in CV in both the emulation and imitation conditions, with the

imitation condition exhibiting the lowest CV. This was not the case for the porcelain trial,

in which each variable exhibited a slightly different CV trend across the three conditions.

Attributes in the porcelain trial instead exhibited variable trends. It is possible that these

variable trends are the result of flaking mechanics of porcelain. For example, platform

thickness in the porcelain trial varied extensively, exhibiting a CV as high as 82% in the

emulation condition. One potential explanation that cannot be ruled out is that knappers

adjusted platform treatment as they became more accustomed to flaking porcelain, which

was a foreign raw material for all knappers. Overall these results reinforce the potential

of raw material to drive lithic variability, even when knappers have similar end goals.

Based only on the basalt trial, it may be reasonably concluded that social learning

tends to decrease variation in stone tools, as proposed by Eerkens and Lipo (2005) and

demonstrated by Schillinger et al (2015). Furthermore, based on the basalt trial, it may be

concluded that watching another knapper can result in more standardized flakes than

copying flakes produced by another knapper. These results lend support to the assertion

that standardization in lithic technologies, particularly Levallois (Lycett, et al., 2016),

required teaching in order to be sustained through time and dispersed across space. These

results also serve as a cautionary tale, demonstrating that some decrease in variation can

occur simply from copying end products of other knappers without direct teaching.

45 The second expectation of this study stated that variables associated with core

reduction strategy would be better predictors of fidelity of information transfer than

variables associated with flake morphology. This expectation was tested by investigating

complexity of flake scar directionality and cortex presence+location as proxies for core

reduction strategy, and platform morphology and thickness evenness as proxies for flake

morphology. The prior variables are expected to show significant differences between the

two experimental conditions while the latter two are not.

Complexity of flake scar directionality confirmed the expectation for both the

basalt and porcelain trials (Table 2-7) in that emulation did not produce flake scar

complexities that were significantly different from baseline for either trial. Imitation, however, did produce flake scar directionalities that differed significantly from the baseline condition. This suggests that the knappers changed their behavior in the imitation condition such that complexity of flake scar directionality was sufficiently altered, and that this shift in behavior did not occur when the knapper was merely copying the flake product in the emulation condition.

Cortex exhibited a similar trend, confirming the expectation, for both trials. There were more flakes with little or no cortex (types 5 and 6) in the imitation condition relative to baseline and this difference was significant in the basalt trial (p = 0.036) and in the porcelain trial (p < 0.001; Table 2-7).

Two proxies were examined that related to flake morphology: platform morphology (thickness/width) (Dibble, 1997; Magnani, et al., 2014; Tostevin, 2012) and thickness evenness (Eren and Lycett, 2012; Presnyakova, et al., 2015). These variables were chosen due to their known relationship to flake morphology as documented with

46 middle-range knapping experiments. It was expected that these two proxies would show no significant differences between the imitation and emulation conditions.

Platform morphology results are consistent with the expectation, and show no significant differences across the experimental conditions (Figure 2-13; Figure 2-14).

This pattern is consistent in both the basalt and porcelain trials. In the basalt trial the platform morphology ratio variance decreased somewhat with fidelity of information transfer. Previous middle-range studies of platform morphology, e.g. (Magnani, et al.,

2014) demonstrate that platform morphology is affected by multiple factors, e.g. angle of blow, external platform angle, percussor type, and force of percussion. It is likely therefore that knappers in this study were constrained by these flaking mechanics such that resulting platform morphology varied little across the different experimental conditions. These results support the hypothesis that platform attributes, although reflective of actual knapper decisions at an individual scale, are not robust proxies for studying cultural transmission in lithic palimpsests. Variation in platform morphology at the assemblage level driven by equifinality cannot be discerned from variation driven by cultural transmission.

Thickness evenness did not meet the expectations for the basalt trial, but it did meet the expectation for the porcelain trial. In the basalt trial, there was a significant difference between the emulation and imitation condition. No other significant differences were observed. In the basalt trial, thickness evenness decreased with fidelity of information transfer. It is possible that thickness evenness decreased with fidelity of information transfer because thickness evenness is itself a measure of standardization (the standard deviation of thickness measurements across the flake). Furthermore, these

47 results indicate that thickness evenness, while considered a variable related to shape, may

actually be a better proxy related to process of reduction. This is because thickness

evenness is affected by multiple geometric processes at once. The results of the porcelain

trial met the expectation in that no significant differences were observed in the three

experimental conditions.

2.6 Conclusions

In this study knappers were asked to create flakes under three conditions. In one

condition knappers were given a 3D model of a flake to copy. In the other condition,

knappers studied a video of an expert knapper carrying out the preferential Levallois

flaking method. These two conditions correlated to the emulation and imitation

conditions, respectively. A control session was also conducted in which the knapper

received no instruction. Two trials were conducted: one using basalt and one using

standardized porcelain nodules.

As a whole, these results lend support to the hypothesis that degree of information

transfer in the social learning of stone tool manufacture are manifested in variables

associated with core reduction strategy. Variables related to end product morphology, particularly platform morphology, were not found to be accurate predictors of degree of information transfer.

These results are best understood when considering tool manufacture as a reductive process with multiple, sometimes competing, geometric constraints. With each strike, the knapper actively makes decisions (e.g. angle of blow, platform depth, and force). These decisions combined determine the overall flake morphology. At a broader scale, the knapper actively decides how to reduce the nodule, i.e. from which direction to

48 remove flakes (centripetal pattern or bidirectional), and how many surfaces to flake.

These decisions combined determine the overall core reduction strategy. The former nest

of decision-making is constrained only by the physics of a single blow, whereas the latter

is compounded for each strike. Thus, as a law of probability, the likelihood of recreating

the results of a single blow by chance are higher than the likelihood of randomly recreating the results of core reduction strategy. Therefore core reduction strategy, and

the variables related to it, should be less susceptible to forces of equifinality than flake

morphology.

Differences were observed between the basalt and porcelain trials. A most likely

explanation for these differences relates to the flaking mechanics of the different

materials. Knappers were accustomed to flaking basalt, whereas porcelain represented a novel raw material for all knappers. Also it is possible that the porcelain nodules were not always heated properly to reach an even vitrification, thereby creating a material that is not sufficiently brittle, elastic, and isotropic for flintknapping. Further work, particularly standardizing the flaking mechanics of porcelain, is needed in order to increase the sample size and draw more robust conclusions.

Another limitation of the study involves the within-subject design, in which knappers participated in all three conditions. It is possible that the knapper ‘learned’, or became more proficient at flintknapping, between the first and third condition in ways that are unrelated to the experimental design, i.e. practice. An ideal experiment would instead enroll unique participants for both the emulation and imitation condition respectively. Additionally, while all recruitment efforts were targeted toward experienced flintknappers, many of the participants (n = 6) had been flintknapping for less than one

49 year and could thus be considered novice (Table 2-9). This variation in knapper skill inevitably affected the results in ways that have not yet been explored.

Secondly, the experiment design created differences between conditions that may be more related to increasing expertise/knapping complexity than specific social input.

The last session included the most information, confounding type of social input with

experience. While it is doubtful that an additional session should explain all reported

differences, this possibility cannot be ruled out. As such it remains an open question

whether or not multiple emulation sessions, each with a unique nodule, could lead to a

reduction pattern like the one observed here for the imitation session (i.e. Levallois).

Thus it remains to be seen if emulators could converge on the observed imitation pattern

through experience and exposure alone, without any specific actions to copy except their

own. A future trial from one ore more experienced knappers learning from others would

shed light on this.

The results of this experiment have direct archaeological application. The CV

results suggest that emulation alone, absent of direct teaching, can affect lithic variability

by reducing overall variation. Therefore similarities in stone tools, particularly flake

morphologies, should not always be considered a result of direct teaching between

individuals. If assemblages from two nearby and contemporaneous archaeological sites

exhibit similar patterns of flake scar direction and technological flake category as

described above, both at a pooled scale and across the reduction sequence, taking into

account local raw material availability, then a strong argument could be made that the

two assemblages formed as a result of culturally transmitted knapping information. The

degree of fidelity of transmission (emulation or imitation) is likely impossible to

50 determine from archaeological assemblages. However given that the patterns in number of directions and technological flake category were consistent for both the imitation and emulation sessions, these results suggest that cultural transmission writ large, regardless of fidelity, is detectable in core reduction strategies.

It is important to remember that all lithic attributes are highly plastic, susceptible to changes in raw material, reduction intensity, nodule size and shape, and knapper skill.

It is only by controlling for these factors that archaeologists are able to begin to understand how cultural transmission is embedded in stone tool manufacture. These experiments are merely the beginning of a middle range line of inquiry. Further work is needed to elucidate these patterns even further, especially increasing the size of the participant pool and having unique participants for the emulation and imitation tasks respectively.

Much likeas Eerkens and Lipo (2005) argued, all potential explanations to artifact variation should be considered before more complex mechanisms, particularly involving direct cultural transmission, are invoked. This is especially the case when comparisons of technologies are made across space and similarities are detected. Technological convergence—that individuals might have randomly re-created similar shapes—should first be ruled out. Even if cultural transmission was responsible for driving artifact similarities, it cannot be assumed that such transmission required direct interaction, because emulative learning is also a possibility.

51 2.7 Supplemental Information

Knapper Years of Hours Per How Experience Capable Familiar ID Knapping Week Participant Studying of with Experience Knapping Learned to Archaeological controlled Levallois? Knap Materials flaking? 1 1-2 0-1 tutor Europe No theoretical instruction- example and direct instruction 2 2-3 0-1 Friend No seen it done on videos a few times 3 2-3 1-2 Took lessons North America Yes with an Expert 4 <1 0-1 took one lesson Africa No with Bill Schindler 6 <1 0-1 took one lesson No with Bill Schindler 7 1-2 0-1 Friend No 11 <1 0-1 experienced No knapper demonstration 14 >4 1-2 Self-Taught North America Yes read, and watched videos 17 <1 1-2 Friend North America Yes 18 <1 1-2 Friend North America No 19 <1 0-1 experimental North America No archaeology class

Table 2-10. Amounts of time that knappers spent in each session (in minutes).

Time Variable Baseline Emulation Imitation Minimum 0:03 0:05 0:09 Maximum 0:08 0:22 0:47 Average 0:05 0:12 0:25

52 Table 2-11. Mass, density, and Young’s Modulus for porcelain cores. Slight differences were observed between the British and domestic clays. Both clays were fired to Cone 10 (1285-1305°C).

Porcelain Group British Domestic All (Standard #257) (Standard #130) n 8 4 4 Average Mass 685.20 670.43 699.98 St Dev Mass 18.10 12.96 3.82 Average Density (g/ml) 2.27 2.23 2.31 St. Dev. Density (g/ml) 0.05 0.02 0.01 Average Young’s Modulus (E) 57.32 55.78 58.86 St. Dev. Young’s Modulus (E) 2.78 2.32 2.53

53 Chapter 3. Measurement Protocols and Three Dimensional Methods: Evaluating Core Reduction Strategy with Photogrammetry

3.1 Introduction

Chipped stone artifacts constitute the most durable residues of Paleolithic human behavior and thus provide a conspicuous mechanism for investigating long-term behavioral change (Isaac, 1976). Currently the nature of the variation in these artifacts is largely “untranslated” (Binford, 1981) because we do not yet have a well-defined understanding of how artifact variation impacts the selective fitness of ancient toolmakers

(Shea, 2011). Our lack of understanding is largely because archaeologists describe variability in terms of categorical units. These units, such as industries, develop out of perceived general patterns but lack empirically defined distinctions (Shea, 2014). Recent approaches to lithic analysis have identified the power of quantifying three-dimensional components of form to explore aspects of technological variation (Bretzke and Conard,

2012; Clarkson, et al., 2006; Lin, et al., 2010). Importantly these approaches allow archaeologists to measure the amount of variation in artifacts, rather than classifying them into groups. One potential concern with recent three-dimensional approaches is that archaeologists have focused on form at the expense of understanding the way in which these artifacts were made (Archer and Braun, 2010; Lycett, et al., 2006; Lycett, 2009). As a result, many of the newer three dimensional approaches have had little impact on studies of lithic variation that focus on technological process, such as chaîne opératoire

(Boëda, 1986; Boëda, et al., 1990; Geneste, 1988; Inizan, et al., 1999; Soressi and

Geneste, 2011).

This chapter develops new methods for quantifying geometric variation in stone tool technology that are specifically tuned to patterns of core reduction that have

54 previously been determined through experimental replication and extensive refitting

studies (Boëda, 1986; Boëda, et al., 1990; Boëda, 1993; Geneste, 1988; Schlanger, 1996).

This study focused on Levallois, or prepared core technology, as it represented a

widespread Stone Age technological approach, comprised of several methods, with

limited geometric variability across space (Lycett and von Cramon-Taubadel, 2013). This study demonstrates how different flaking methods (i.e. preferential Levallois, discoidal) can be distinguished using a series of three-dimensional geometric variables. When applied to archaeological data, however, the variables that distinguish these methods vary substantially within a specific archaeological assemblage. This suggests that the current description of technological strategies may obscure more complex underlying variation.

Moreover, there is a large disconnect between how the Levallois methods were first described and how they are used today. This chapter proposes that instead of using technological categories—like Levallois—archaeologists should focus on empirical measurements that describe technological variation.

3.2 Background to Levallois study

The preferential Levallois reduction strategy is considered to have implications for planning and cognitive complexity (Schlanger, 1996; Wynn and Coolidge, 2004).

This is because the preferential Levallois method is characterized by a series of flakes removed in a sequential pattern, such that the final flake is often referred to as

“preferential” (although there is a diversity in the types of different approaches to

Levallois). Experimental studies suggest Levallois technology minimizes raw material waste while maximizing edge length (Brantingham, et al., 2000; Brantingham and Kuhn,

2001; Lycett and Eren, 2013a; Wallace and Shea, 2006), or to maintain core shape

55 throughout reduction (Eren and Bradley, 2009; Sandgathe, 2004) and results in flakes

with less variable edge angles (Eren and Lycett, 2016) that are evenly thin (Eren and

Lycett, 2012). The Levallois production sequence also has implications for social learning and population dynamics (Lycett and Norton, 2010; Mithen, 1997) and its spread may have required teaching (Lycett, et al., 2016; Ranhorn, et al., 2015). Given the importance of Levallois technology, it is critical that archaeologists can systematically identify the features of this method in the archaeological record, in ways that incorporate internal and external reliability (Lycett and Eren, 2013b). Perpère (1986) demonstrated

the inter-analyst unreliability lithicists face when asked to identify Levallois flakes (the

study did not include cores) (Table 3-1). This is problematic because—in any academic

field—a definition is only as useful insofar as it can be formally applied. For Levallois

technology, the most widely used definition among archaeologists is Boëda’s (1995) volumetric conception.

Boëda% Tuffreau % Perpère %

Levallois 29.3 40.1 49.5 Non-Levallois 52.0 54.5 50.5 Unknown 18.7 4.5 0

Boëda’s (1990, 1993, 1995) volumetric conception describes the holistic

technological process of creating a Levallois core. Importantly, Boëda’s description does

not focus on the final form of the Levallois core but rather the way in which it was

produced. Generally, it is the most commonly applied definition of this technology

(Adler, et al., 2014; Lycett, 2009; Tryon, et al., 2005), and is comprised of four specific

56 factors (Figure 3-1). Even the earliest descriptions of Levallois technology (Commont,

1910) define it as a flaking strategy divided into two opposed surfaces. The removal of mass in these two opposed hemispheres forms a line of intersection (I) where the two planes meet. Such cores, with two opposed surfaces, are also a feature of bifacial flaking, commonly attributable to handaxe production [e.g. Isimila (Howell, 1961), Olorgesailie

(Isaac, 1977), Bose (Yamei, et al., 2000)], as well as some smaller bifacial points [e.g.

Blombos (Archer, et al., 2015), Aduma (Yellen, et al., 2005), and ≠Gi (Brooks, 1978)].

However, unlike many of the bifacial technologies, the Levallois flaking strategy is organized such that the two opposed surfaces are hierarchical (II). That is, one surface is preferentially flaked (upper hemisphere) while the other surface is prepared in a way that creates a striking platform (lower hemisphere) for removals on the opposite surface.

Often the lower hemisphere is worked so minimally that it is partially or entirely cortical.

Boëda also described the maintenance of distal and lateral convexities of the production surface as a crucial step to enable the removal of an elongated thin

(preferential) flake (III).

Finally, Boëda argued that the flaking plane of the upper surface is sub-parallel to the plane of intersection (IV).

In some publications, Boëda (1995) referred to a fifth requirement in which the axis of the upper flaking surface was perpendicular to the “hinge”, or striking platform, and a sixth requirement, hard hammer percussion. However these criteria are not discussed here.

The four criteria outlined above define Levallois methods as a series of patterned flake removals rather than a specific core form. Therefore it is difficult to identify this

57 method of reduction from core forms alone. To better understand how technological decisions influence attribute analysis of lithic byproducts, this study created experimental

Levallois cores by following Boëda’s definition, and used 3D shape analyses to determine morphological traits that are sensitive to the technological principles outlined by Boëda. Given the geometric nature of Boëda’s definition, 3D analyses are particularly well suited to highlight these relationships.

58 3.3 Materials and Methods

Table 3-2. Characters measured in this study and expectations using Boëda’s volumetric conception.

Characters Measured Expectation based on Boëda’s volumetric conception in this Study Variable 1: Volume Levallois cores will have a smaller upper: lower volume ratio ratio (upper: lower) than non-Levallois cores The ratio of the angles between flake scars on the upper Variable 2: Flake angle surface and flake scars on the lower surface will be smaller in ratio (upper: lower) Levallois cores compared to non-Levallois cores The angle between the removal of the “primary product” and Variable 3: Flake angle the plane of intersection between the upper and lower surface primary products will be smaller for Levallois cores than non-Levallois cores

This study used a series of 3D techniques to document variation in Levallois technology. The author developed a protocol by first translating Boëda’s criteria to geometric variables that can be applied to 3D models of cores. This protocol was then used to analyze experimental and archaeological cores. Photographs that were used to make the photogrammetric models of cores were captured using a Nikon D3100. 3D photogrammetric models were developed in Agisoft Photoscan Professional with a minimum of 200,000 polygons. The models were aligned and registered in GeoMagic

Studio 2014. Finally, the cores were analyzed in GeoMagic according to a standard protocol taking into account each of Boëda’s criteria. This protocol was then tested for inter-observer replicability by a researcher unfamiliar with the project.

3.3.1 Geometric Analogies for Boëda’s Geometric Conception

Plane of Intersection

“Le volume du nucleus est conçu en deux surfaces convexes asymétriques, sécantes, délimitantes un plan d'intersection.” Boëda (1993). (The volume of the core is conceived

59 in two convex asymmetrical surfaces, secant to each other, delimited by a plane of

intersection.)

A plane here is defined as a series of x, y, z points which all have in common one

coordinate (in this case z) with variance in the other two dimensions (x and y). This

enables objective extraction of the plane of intersection of an artifact (usually a flaked piece or core) by displaying it into a cartesian coordinate system. This study used photogrammetry and blue light laser scanning to capture the 3D shape of these cores,

although other 3D methods may also be sufficient, from cross beam caliper coordinates

(Lycett, 2009) to multi-light laser scanning (e.g. NextEngine) (Shipton, 2010).

In this study the plane of intersection between the upper and lower hemisphere was extracted by placing evenly spaced markers along the ridge formed along the circumference of a core. This intersection is defined by the flake scars that initiate along this division. Flakes have been removed in both directions along this division. The flaking ridge (aris) was defined sensu lato as a line formed where flaking surfaces intersected. This general approach enabled us to capture the plane of intersection for cores with more than two flaking surfaces (e.g. multiplatform, ad hoc). While such cores were rare in this particular study, they are present in many archaeological samples. The selection of specific points on a ridge avoids potential bias that could be introduced based on prior assumptions of core structure. This system creates a geometrically defined rather than technologically defined core orientation. Each selected marker is defined by x, y, z coordinates on the 3D model of the core. The plane of intersection is calculated as the least squares plane between the markers. Defining this plane of intersection orients the core into two opposed hemispheres (Figure 3-1A).

60 It is next necessary to determine the geometric orientation of the two flaking

surfaces relative to each other. According to Boëda (1995), “the two surfaces are hierarchical, such that one surface serves as the plane of flake production (débitage)

while the other serves as the plane of striking (frappe)”. If the two planes represented differential flaking strategies, such a pattern should be visible geometrically in the reduction of volume. Furthermore, this geometric approach can only highlight differential use of the two faces; hierarchy, which implies an order of use, cannot be empirically demonstrated with this method but instead requires refitting studies to accurately capture order. To test for differential volume of flaking surfaces, the relative volume and relative flaking angles of the two hemispheres were measured (Table 3-2; Figure 3-1; variable 1 and 2).

Volume

A primary expectation of this study states that if the two flaking surfaces were exploited differently, this relationship will be exhibited through differential volumes of the two flaking surfaces. To maximize standardization, the cores were geometrically oriented such that the hemisphere with the lowest volume was oriented as the “upper surface” with regard to the plane of intersection. Using the 3D model and the plane of intersection defined as above, volume of the core above and below the plane of intersection for all cores was measured. From this, the relative volume ratio (ULVR:

Upper surface relative to lower surface volume ratio) was measured for all cores. A

ULVR value of 1 indicates that both hemispheres have equal volume, while a ULVR value of 0.5 indicates that the upper volume is half the volume of the lower hemisphere.

Based on Boëda’s (1995) volumetric conception, it is expected that cores produces via

61 the Levallois method will exhibit a significantly lower ULVR than cores resulting from

the discoidal method. Specifically, it is expected that cores produced via the Levallois

method on average will have more asymmetric volumes than those produce via discoidal methods.

Flaking Angles

The angle between flaking surfaces is clearly an important feature in the

development of certain technological strategies (Dibble and Rezek, 2009). Boëda (1995)

argued that in Levallois technology the angle of the primary flaking surface is sub-

parallel to the plane of intersection (criteria IV). This study therefore developed a method

for understanding relative flaking angles on 3D models. First planes of individual flake

removals were extracted by placing evenly spaced markers along the flake scar outline.

Next, the angle between each individual plane (i.e. flake scar) relative to the plane of

intersection was measured. Averaging these values for a particular hemisphere of the core

yields the upper angle average (UAA). Comparing UAA with the average angle of the

lower hemisphere yields the upper: lower angle ratio (ULAR). A ULAR of 1 indicates

that the average flaking angles of both hemispheres are equal, while a ULAR of 0.5

indicates average flaking angle of the upper hemisphere was half that of the lower

hemisphere. Based on Boëda’s definition (1995) it is expected that coreds produced via

the preferential Levallois method will exhibit lower ULAR values than those produced

via discoidal methods. Boëda (ibid) also argued that the primary flaking plane was sub-

parallel (secant) to the plane of intersection. This was investigated by measuring the

relative angle of the primary flake angle (PFA). The primary flake was identified as the

62 largest flake scar on the “upper surface” for both experimental Levallois and

experimental discoid cores.

3.3.2 Replicability

To determine the extent to which these variables can be measured across multiple analysts, an inter-analyst test of variation was conducted. To avoid bias, an analyst unfamiliar with the goals of this research project was trained to implement the 3D protocol and collected an independent dataset. The inter-analyst study compared variance in the ULVR, ULAR, and PFA on 10 cores from the site of Skhūl (McCown, 1937).

These data were analyzed with linear regression and paired t-test to determine reliability of results.

3.3.3 Materials

Experimental and Archaeological Samples

To create the experimental assemblage, expert flintknappers were told, “Please

produce flakes according to the Levallois reduction scheme or the discoidal reduction

scheme,” following Boëda (1993; 1995). Knappers were given no further instruction.

Experimental reductions were performed on a variety of raw materials based on local

availability, and included Bergerac flint, Oregon basalt, and Potomac River quartzite

cobbles. Knappers were recruited from established flintknapping groups, two from a

lithics workshop in Les Eyzies, France, one from an experimental archaeology workshop

in Atlanta, Georgia, and two from primitive technology knapping sessions in northern

Virginia.

Archaeological materials (n=30) in this study derive from Skhūl, part of the Mt.

Carmel cave complex in Israel, which was excavated by Theodore McCown in 1931 and

63 1932, and are currently stored at the Harvard Peabody Museum of Anthropology and

Ethnology. The specimens included in this study derive from Skhūl levels B1 and B2,

dating to 81-131 ka (Grün, et al., 2005; Mercier, et al., 1993; Stringer, et al., 1989).

McCown (1937) and Garrod and Bate (1937: 109-111) recorded a total of 1,355 Levallois

cores in Skhūl B and described these cores as having overall little variation in size. All

cores in this study were of cryptocrystalline silica (“flint”).

3.4 Results

The Skhūl collection (n=30 cores), experimental Levallois cores (n=10) and experimental discoid cores (n=6) resulted in 46 photogrammetric models for digital morphometric analysis.

3.4.1 Inter-analyst variation

Inter-analyst error was tested for six variables: upper volume, lower volume, volume ratio, upper flake angle average, lower flake angle average, and average angle ratio.

For each measurement we a non-parametric paired Mann Whitney signed rank test was used to examine the similarity in the two independent datasets. A p value > 0.05 for all variables indicates that it is not possible to refute the null hypothesis that the two datasets derive from the same population.

Table 3-3. Inter-analyst reliability tests (n=10).

Variable V P value Upper Volume 31 0.770 Lower Volume 22 0.625 Volume Ratio 33 0.625 Upper Angle 16 0.275 Average

64 Lower Angle 19 0.432 Average Angle Ratio 20 0.492 All Data 715 0.142

3.4.2 Experimental assemblages

It was first determined the extent to which the variables measured distinguish

between cores produced via Levallois and discoidal methods. In terms of volume, our

experimental Levallois cores exhibited a volume ratio range from 0.24-0.59, while

experimental discoids exhibited a higher range from 0.48-0.75 (Figure 3-2A). Therefore our experimental results indicate that Levallois core upper volumes are less than half of corresponding lower volumes, while discoid core upper volumes are over half of the lower volume. Mann-Whitney U-test of equal medians shows a non-significant, yet trend

level, p-value of 0.057.

Regarding flaking angles, experimental Levallois cores exhibited an angle ratio

range from 39.25 – 13.16 while discoids exhibited a higher inter-quartile range from

0.70-1.12 (Figure 3-2B). A test of means showed a significant difference (p=0.006, Mann

Whitney U=4).

Experimental Levallois cores also had more acute upper flake angle averages than experimental discoids and this difference was significant (Figure 3-2C) (p=0.002, Mann-

Whitney U = 2).

This variable is technologically analogous to what Boëda described as the angle

of the preferential flake. The primary flaking angle of our experimental Levallois cores

exhibited inter-quartile range of 17.84-24.54 while experimental discoid cores exhibited

65 an inter-quartile range of 32.78-45.00. These represent significant differences in the primary flaking angle (p=0.004, Mann Whitney U=3) (Figure 3-2D).

3.4.3 Archaeological assemblage (Skhūl)

nextN determined was the extent to which the variables measured varied in an actual archaeological assemblage (Skhūl). Skhūl showed a ULVR range that is significantly different from both the experimental Levallois (p < 0.01, U=338) and

67 experimental discoid (p < 0.001, U = 268) groups (Figure 3-3). The Skhūl ULVR inter-

quartile range (0.20 – 0.39) overlapped partially with the experimental Levallois group

while almost half of the Skhūl data points fell below the Levallois range (i.e. more

hierarchical). The Skhūl ULVR inter-quartile range did not overlap with that of the experimental discoid group.

In terms of flaking angles, Skhūl differed significantly in ULAR from that of the experimental discoid group (p < 0.001, pair-wise Mann Whitney U = 271) (Figure 3-3B) but there was no significant difference between the Skhūl ULAR range and that of the experimental Levallois group (p=0.21, U = 269). This trend also applied to the average upper flaking angle (Figure 3-3C). The Skhūl UAA range differed significantly from the experimental discoid group (pair-wise Mann Whitney, p < 0.001, U = 248) and overlapped with the experimental Levallois group (p=0.56, U = 242).

Focusing only on the primary flake angle (PFA), Skhūl exhibited a similar trend, in which the PFA range was significantly different from that of the experimental discoid group (p<0.001, U = 247) and was also different from the experimental Levallois group

(p=0.041, U = 135), although these two ranges did overlap (Figure 3-3D).

3.5 Discussion

69 3.5.1 Experimental assemblages

Figure 3-2A indicates that cores produced via Levallois reduction methods have a smaller relative volume than those produced via discoidal methods. This geometric discordance is technologically analogous to differential flaking treatment of the two faces, in which one flaking surface is flaked differently from another, affecting the remaining volume of the two hemispheres. Both Levallois and discoid cores converge at a ULVR range of 0.5, indicating that is possible for both forms of flaking to result in a core in which the upper volume is half of the lower volume. However, when analyzing the scale of variation at the assemblage scale, the range of ULVR values for experimental

Levallois cores was generally below the 0.5 threshold. Discoids generally had a range of values that exceeded 0.5. This demonstrates the importance of considering ranges of values rather than only reporting averages or medians.

Figure 3-2B shows the different angle ratio ranges for experimental Levallois and experimental discoid cores, confirming that the sub-parallel flaking of the upper surface is discernible in the remaining core. ULAR is thus another measure that can be used to quantify hierarchy in Paleolithic assemblages. One experimental Levallois core in our sample was a clear outlier with ULAR=0.91; further review of this particular core revealed it had 5 flake removals on the upper surface, one of which had a flake angle less than 10 degrees while the other four were well over 35 degrees. The smaller angle is consistent with what Boëda and others described as a preferential flake removal, while the other steeper removals may have been removed to maintain the distal convexity. Thus it was possible for Levallois and discoid cores to overlap in terms of ULAR, particularly

70 in instances where the final removal did not remove convexity maintenance scars. This

demonstrates the importance of observing the range of ULAR within an assemblage.

The study also compared the average flaking angle of the upper surface (UAA)

for both experimental assemblages (Figure 3-2C). For Levallois cores, this variable is

technologically analogous to the average angle of the flake production surface. Based on

Boëda (1937-111) it was expected that Levallois cores will exhibit a more acute UAA

than discoids. Experimental results confirmed this observation. One experimental

Levallois core showed an outlier UAA of 39.25 degrees, resulting from the maintenance

of distal convexity as described above. Thus UAA in itself can be a good indicator of

hierarchy in archaeological flaking strategies.

In terms of the primary flake removal, PFA was expected to be smaller (i.e. more

parallel with the plane of intersection between the two hemispheres) for experimental

Levallois cores than experimental discoids and this pattern was confirmed (Figure 3-2D).

Skhūl

Given that Skhūl is a Middle Paleolithic site with a strong documented degree of

prepared core reduction (Leslie, 2008), it was anticipated that Skhūl would exhibit a

ULVR range within the experimental Levallois range and outside of the experimental

discoid range. This relationship was confirmed to some extent. There were significant

differences between Skhūl and both experimental assemblages, but this significance was

weaker with experimental Levallois (alpha < 0.05) and more pronounced with

experimental discoid (alpha < 0.01). It is important to note that the inter-quartile range for

Skhūl overlapped with that of the experimental Levallois assemblage, but did not overlap with the inter-quartile range of experimental discoids. There were two outliers in the

71 Skhūl sample, both of which were slightly obscured by calcrete concretions (> 2mm

maximum diameter). Thus although post-depositional processes introduce an unavoidable

bias in all archaeological assemblages, this method enables the analyst to visualize the

full range of variation and pinpoint outliers that may have been particularly affected by

these processes.

In terms of flaking angles, the Skhūl sample also fell in line with the experimental

Levallois group, both of which had overlapping inter-quartile ranges. The Skhūl sample

ULAR was significantly different from the experimental discoid range (alpha < .001).

The average upper angle for Skhūl exhibited an inter-quartile range that fell completely within the inter-quartile range of the experimental Levallois assemblage

(Figure 3-3C). However, one of the Skhūl outliers fell within the experimental discoid group (UAA=36.4).

The average primary flake angle of the Skhūl assemblage overlapped somewhat with that of the experimental Levallois group but the two datasets were significantly different (W = 135; p = 0.041). This is especially interesting as the experimental

Levallois assemblage consisted only of preferential Levallois cores. Given the potentially palimpsest nature of the Skhūl assemblage, a higher range of variation for PFA of Skhūl was expected, reflective of diverse Levallois core reduction strategies (e.g. recurrent, centripetal). Results support this expectation, showing a range of variation of PFA for

Skhūl exceeding that of the experimental Levallois group (W = 135; p = 0.041). The increased variation in the Skhūl sample may also be due to a difference in sample size.

Variation of Skhūl did not overlap with the experimental discoid group.

72 3.5.2 Paleolithic variability

Figure 3-3 shows ranges of variation (with individual values jittered so they are visible within the overall dataset) for the reported variables in the Skhūl assemblage relative to the experimental ranges. It is important to note that as the assemblage-scale range trends toward the experimental Levallois range, there are some outliers. Also while one core may fit the Levallois definition according to one variable, it may not satisfy all four criteria, as shown in Figure 3-4 in which a single core is highlighted for all variables.

This is due both to the interplay of the technological variables in question and also the variable extent to which the different cores have been reduced. This demonstrates how categorical variables (or technological descriptions, such as Levallois) can obscure underlying variation that is a key feature of Paleolithic assemblages (O’Brien, et al.,

2008; Shea and Bar-Yosef, 2005). When stone artifact variation is dissolved into technologically relevant quantified variables then the focus of analysis can be placed on the diversity within assemblages. This type of study allows the explication of technological trends in stone artifact assemblages that would otherwise be unobservable with approaches that focus on categorizing artifacts into specific typological and technological groups. This approach can be used to compare across sites, especially when time, raw material, and reduction intensity are factored into the analysis.

Figure 3-4. Experimental and Skhūl ranges. The yellow star highlights a single core from Skhūl for each of the four variables.

3.6 Conclusions

Comprehensively, these results demonstrate a means to measure signatures in lithic byproducts that are related to specific features of technological core reduction processes. This study provides one example of how traditional technological studies and more recent 3D morphometrics can be combined to provide insights that are difficult to isolate with each of these approaches separately.

74 By focusing on the geometric relationships proposed by Boëda for preferential

Levallois flaking strategy, this study also developed a template of expectations against which archaeological materials can be analyzed. The Skhūl sample, as expected, is more similar to the experimental Levallois sample than to experimental non-Levallois sample for all variables.

Importantly, however, individual cores from Skhūl vary in their adherence to the four different Levallois criteria. A core may have a volume that exhibits significant hierarchical distinction between hemispheres but the removals on either side of the plane of intersection may be relatively similar (Skhūl #27; Figure 3-4). This result is not surprising considering the multiple geometric processes that are at work throughout a reduction process. Technological categories such as “Levallois” are actually represented by multiple geometric relationships that vary despite frequently similar median patterns.

The use of categories (i.e. discoid, Levallois, Mode III) to describe these general similarities obscures technological variation. It is postulated here that instead of placing artifacts into categories like “Levallois”, archaeologists should focus on empirical measurements that describe the technological variation. Measurements like volume, flake scar pattern, and flaking angles of hierarchical flaking strategies are only a few examples of this approach. These variables are better at predicting reduction method than the analysts in Perpere’s study (Figure 3-5). The advantage of a focus on variation within technological systems is that it allows archaeologists to identify subtle variations through time that may reflect drift or selection on certain forms (O'Brien and Lyman, 2000).

not” (O'Brien and Lyman, 2000) (Sellet, 1995) nor are they meant to be applied to

individual artifacts. Clearly, the definition of Levallois requires a comprehensive

investigation into the entire reduction process (Boëda, et al., 1990) (Sellet, 1995). Rather,

our method can be used to view general patterns in hierarchy of core reduction and is best

utilized when studying ranges of variations within and across assemblages. By isolating

specific technological variables, this method allows the quantification and identification

of variability within technological strategies. Further work investigating how these

variables are affected by reduction intensity is needed. In general, these approaches

emphasize materialist approaches as opposed to more empiricist agendas (Boëda, et al.,

1990; Lycett, et al., 2016; Picin and Vaquero, 2016) and can be used to explore

standardizations and diversity in Paleolithic assemblages.

76 3.7 Supplemental Information: 3D Capture and Analytical Protocol

3.7.1 Capture

This study used a Nikon D3100 to capture all cores. Cores were placed on a plain or gridded surface with a scale and captured by taking two sequences of 15-30 photos in rotation around the each of the two opposing flaking surfaces.

Preparing for Import into GeoMagic

In order to import a photogrammetric model into analytical software it is

necessary to use the correct file format. Sometimes this requires conversion. For example

models from Agisoft Photoscan use .psz format. In order to be imported into GeoMagic

the .psz file must be converted to a format recognized by GeoMagic such as .wrl.

However, before exporting the model as a .wrl check the resolution and set the scale.

In Agisoft Photoscan:

• Check model

o It is useful to check the number of polygon faces and make sure it is a high-resolution model. This study uses 200,000 polygons per face.

o Check for holes or gaps in the model. Also check alignment: . Under the Photos pane, change list view to details and it will

display a check mark if the photo is aligned as well as the quality.

If several are unaligned it may require new photographs.

• Set scale

o Setting the scale is a crucial step. There are several ways to do this.

o Zoom into the scale on the 3D model itself.

77 . Note: Theoretically this point should be based on the three-

dimensional data of multiple photographs and will be the most

similar to the size of the model. One can also choose an orthogonal

photo of the scale, but it is unclear how much distortion occurs

from single photo to the model. See (Biermann, 2014)

o Right-click a point on the scale and choose “Create Marker.” Do this again for the second point.

o Set Scale Size . Make sure Ground Control is visible by going to View  Panes 

Ground Control

. Under the Markers pane, select the two points just created (use

shift to select both). Right click on the selection and choose

“Create Scale Bar.”

. Enter the distance in meters e.g. 1cm = 0.01m

. Hit Enter

. This study used four markers on the scale bar to ensure scale

accuracy.

. Important! Click the “Update” button on the Ground Control

toolbar. The symbol is two arrows in a circle.

o Save

• Export model into GeoMagic compatible format

o File  Export Model . Files of Type: VRML models (*.wrl)

78 Merging two sides of model (e.g. dorsal and ventral) in GeoMagic:

In this study two photogrammetric models were created for each core, one of each face.

This is to ensure all surfaces are properly modeled; not doing so will inevitably create

missing information (holes) at the point of contact where the core meets the surface. For

several analyses, e.g. volume, the model must be merged into a single dense point cloud.

Otherwise the two point clouds of the dorsal and ventral sides will be analysed as two

individual units. *Not all 3D analyses require this step. If the question can be answered

with a photogrammetric model produced from a single view it probably advisable, as

merging two models will undoubtedly introduce more error/distortion to the model

(Magnani, et al., 2016). It is therefore important to have an independent analyst create new models and merge them independently to confirm your results.

In GeoMagic Studio:

• Open file

o Click main Studio button in upper left corner  Open  Open . Choose File e.g. KF003A_scaled.wrl

• Bring in the other view of the model

o Studio button  Import . Choose other file e.g. KF003B_scaled.wrl

• Align models

o There are multiple ways to do this. Copy the two independent models within the Model Manager to keep as originals in case the Alignment fails.

o For a quick and easy alignment use the “Best Fit Alignment”

79 . Select just one of the models in the Model Manager. This will be the

base model.

. Click the “Alignment” ribbon

. Choose “Best Fit Alignment”. Click OK.

• If the alignment looks good, click Apply

o For a more user-based alignment method use “N-Point Alignment”. Here the user chooses homologous markers and can use as many as considered

necessary. It is useful to use markers within the 3D model of known distance.

The more homologous markers you use, the more accurate your model will

be.

• Merge

o Once aligned, click the “Polygons” ribbon and click Merge.

Capturing features and obtaining data.

Define plane of intersection

• Make sure the merged version of the model is selected in the pane on the left.

• Click the Capture Ribbon.

o Click Plane

o Set markers . The plane will be defined as the least squares distance of the x and

y values of all of your markers. A plane can be defined by a

minimum of 3 points, however in this study a marker was placed

every ~1cm. It is important to be consistent and not place more

80 markers on one side than the other, as this would make the plane

be weighed more heavily by those x and y values.

o When finished, click the space bar, and the newly defined plane will be displayed.

o In the Model Manager you can rename this plane e.g. Plane of Intersection by double clicking on the plane name.

Measure volume

Once a single dense point cloud and defined plane is obtained, it is possible to measure the volume of the point cloud relative to the plane:

• Analysis ribbon

o Compute  Compute volume to plane

o Define plane: Object Plane . Choose the plane you created, e.g. Plane of Intersection

. The volume above and below the plane will be displayed. Enter

into the database.

Set flaking angle planes

The next step in this analysis investigates the relative angles of the flaking surfaces. To do this, extract a plane for each individual flake scar > 2cm. Extract the plane in the same way as described above, but this time following the flake scar ridge (aris).

• Remember to click Space Bar to define the plane. Remember to name each plane

e.g. UF1 “Upper Flake 1”. This will be tied to data later on.

• Once the planes are set, several attributes can be measured for each flake scar,

such as angle:

81 o Capture ribbon o In the box called Measure and choose, choose Plane-Plane angle. The symbol is two planes with an arrow. o Select two defined planes of interest, e.g. Plane of Intersection and UF1. . It is helpful at this step to hide all of the planes except the ones

being measured to ease selection.

. On the display box it will say:

• Dimension between Plane of Intersection and UF1:

o Angle XX.XX

o Enter into database

o Repeat for all upper and lower flake angles

82 Chapter 4. Re-thinking Regional Identity in the Middle Stone Age with Behavioral Approaches to Cultural Transmission (BACT)

4.1 Introduction: The Current State of MSA Research

The MSA in the broadest sense is a technological stage of human behavioral

evolution that followed the Early Stone Age and preceded the Late Stone Age. This tri-

partite system of African technological evolution was developed by Goodwin (Goodwin

and Van Riet Lowe, 1929; Goodwin, 1928; Goodwin, 1929; Volman, 1981), who discerned the MSA based on the abundance of flake based tools, as opposed to the core based tools that characterize the Early Stone Age, combined with the lack of microlithic tools that characterize the Late Stone Age. The MSA is not a time period, but is broadly contemporaneous with the later Middle Pleistocene and the Late Pleistocene. As

Goodwin described, variable flake tools including retouched flakes, scrapers, denticulates, and Levallois flakes characterize the MSA, like the Middle Paleolithic of

Europe. For this reason, some argue that the MSA began by ~500ka with the earliest

Levallois points at Kathu pan in South Africa, although the degree to which these points were contemporaneous with bifacial reductions, and therefore classified as Fauresmith, considered transitional to the MSA, is under debate (Wilkins, et al., 2012). The “end” of the MSA is not well defined, and tends to coincide with the proliferation of backed microliths (Ambrose, 2002) ~40ka or older. In sum, the MSA writ large is a designation based historically on lithic technology. As such, its definition and use varies across researchers.

Of course, the meaning of the MSA has changed substantially since its inception.

For decades MSA research focused extensively on patterning across space (Leakey 1931,

1935; Clark 1954; Volman 1981; Mehlman 1989), eventually propelling J.D. Clark to

83 propose the MSA as basis for the origins of “regional identity” (1988). Therefore, a

narrative regarding the emergence of “modern human behavior” dominated the MSA for

some time. These debates centered on the technologies that emerged in the MSA, the

timing and tempo of their emergence, and the extent to which they did or did not

represent technologies that are deemed behaviorally modern (Deacon 1989; Klein 2001;

Henshilwood et al 2001; D’Errico 2003). McBrearty and Brooks in 2000 demonstrated in great detail that the traits previously considered to define modern humans in Europe actually appeared in the African MSA much earlier than previously thought. The known

MSA record today spans the entire continent of Africa (Richter, et al., 2017; Scerri, et al.,

2014a; Scerri, et al., 2016; Soriano, et al., 2010) but is best known from sites in southern and eastern Africa.

4.1.1 The South African MSA record—Howiesons Poort, Still Bay, and Technological

Change

For several decades MSA research predominantly focused on the southern coast of South Africa, in which clear demarcations of technological change were well documented (Mackay, et al., 2014; Volman, 1981). Sites such as Klasies River Mouth

(Wurz, 2000; Wurz, 2002; Wurz, 2013), Blombos (Henshilwood, et al., 2001;

Henshilwood, et al., 2009) and Pinnacle Point (Marean, et al., 2007) provided key sequences by which the tempo and pattern of technological change were revealed. These data suggested that toolkits dominated by bifacial lanceolate points, commonly referred to as the Still Bay (SB), disappeared, followed shortly thereafter by the emergence of the

Howiesons Poort (HP), characterized by small backed blades. This change, researchers argue, may have taken place in less than 10,000 years (Jacobs, et al., 2008) although

84 others (Brown, et al., 2012) argue that the ‘flickering’ signal of the HP is caused by a lack

of well-dated sites. However, publications on sites beyond the southern coast go back

earlier than many of the coastal sites, such as Border Cave (Villa, et al., 2012),

Boomplaas (Deacon, 1979), Diepkloof (Parkington and Poggenpoel, 1987), and Rose

Cottage Cave all help evaluate the HP, and particularly the “post-HP” technocomplex

(Soriano, et al., 2007; Wadley, 1991). Cave of Hearths and Florisbad (Kuman and Clarke,

1986) provided modern human skeletons and less well studied lithic assemblages.

Several hypotheses derive from this well-studied record, including Curtis

Marean’s theory that the modern human progenitor population lived in South Africa

(Marean, 2010) and that the defining characteristics of modern human behavior are the

result of systematic coastal foraging adaptations (Marean, 2014). More recent discoveries

at Diepkloof (Porraz, et al., 2013a; Porraz, et al., 2013b; Tribolo, et al., 2009; Tribolo, et

al., 2013), Sibudu (Will, et al., 2014), Kathu Pan (Wilkins and Chazan, 2012; Wilkins, et

al., 2012) and Vleesbai (Oestmo, et al., 2014) all further force a reexamination of the definitions and temporal context of South African cultural-stratigraphic units, and question the primacy of proposed southern coast adaptations in modern human behavioral evolution. In sum, new explanations of MSA variability are needed (Conard, et al., 2014).

To test these ideas systematically, a broader understanding of the tempo and pattern of

technological change in the rest of Africa is needed.

4.1.2 Beyond the Cape—MSA Research in Central and Eastern Africa

Important and informative MSA research spanning the continent can be traced back

several decades. Mumba Rockshelter has provided perhaps the longest sequence of

technological change in the Eastern African MSA and has been studied by several

85 researchers (Diez-Martín, et al., 2009; Gliganic, et al., 2012; Mehlman, 1989;

Prendergast, et al., 2007). Both Nasera (Leakey, 1936; Mehlman, 1989) and Kisese II

(Inskeep, 1962), studied for this dissertation, also provided MSA and MSA/LSA key sequences in Tanzania. In Kenya, the Kapthurin provides one of the earliest accepted ages for the MSA (~285 ka) and is marked by a complex stratigraphy, possibly inter-

digitated with Acheulean layers (Tryon, et al., 2006). Gademotta in Ethiopia further

confirmed the antiquity of the Eastern African MSA and provided evidence for early

projectile weaponry (Sahle, et al., 2013; Sahle, et al., 2014). Aduma (Yellen, et al., 2005)

yielded highly diverse reduction strategies, changing raw material use, and one of the

earliest examples of “microlithic” production.

Later MSA sequences are especially abundant in the Kenyan Central Rift near Mt.

Eburru such as Prospect Farm (Anthony, 1978) and Prolonged Drift (Merrick, 1975).

Cartwright’s Farm (Waweru, 2007) and Gamble’s Cave (Leakey, 1931) also provided

MSA and MSA/LSA sequences, although studies of these assemblages have focused

mainly on their Holocene deposits.

Research north of the Limpopo and south of the Rift Valley also provides crucial

evidence to the study of modern human origins. In Namibia, White Paintings Shelter of

the Tsolido Hills provided a 7 m sequence (Robbins, et al., 2000) and Apollo 11 provided

evidence for the oldest portable art in Africa (Vogelsang, et al., 2010). Excavations at

≠Gi, a pan in the Dobe Valley in Botswana, documented dense MSA and LSA

assemblages including bifacial points and provided a geoarchaeological history for the

sequence (Brooks and Yellen, 1977; Helgren and Brooks, 1983). Broken Hill (Kabwe)

not only revealed a remarkable cranium, potentially attributed to H. heidelbergensis, but

86 also bone points potentially attributed to the MSA (300-120 ka) (Barham, et al., 2002).

Barbed and unbarbed points were also discovered in the Democratic Republic of Congo

(DRC) at Katanda (Yellen, et al., 1995) and are dated by various methods to ~90 ka

(Brooks, et al., 1995). Excavations at Mumbwa Cave revealed a hearth (Barham, 1996)

and windbreaks (Barham, 1995). Potentially backed points at Twin Rivers and Kalambo

Falls further require us to question the origin and spread of culture-stratigraphic units like

the HP (Barham, 2002). Within Zimbabwe alone, Pomongwe and Tshangula (Cooke,

1963), and Bambata (Armstrong, 1931) of the Matopo Hills, Khami Waterworks near

Bulawayo (Cooke, 1957), and Zombepata (Cooke, 1971), a painted cave in Mashonaland,

all revealed sequences that collectively comprise industries that Cooke referred to as the

Bembesi (Sangoan), Charama (proto-Stillbay), Bambata (Still Bay), Tshangula

(Magosian), Khami (Wilton) and finally bantu (Cooke, 1971). While mostly undated,

these sites in Zimbabwe likely span the MSA, MSA/LSA transition, and the terminal

LSA into the Holocene.

In sum, more and more lithic sequences are produced from different caves and

open-air sites every year, which themselves require significant funding and time. While

research dollars to excavate new sites is promising, very little investment has gone

toward synthesizing the information already available, or re-dating excavated sites to

form a broader understanding of human behavioral evolution. That Africa is several magnitudes larger than Europe, and yet researchers continuously try to frame African

Paleolithic technology in terms of European-like replacement culture histories (e.g.

Leakey, 1931; Porraz, et al., 2013b; Will, et al., 2014), exemplifies this issue.

87 One consensus among Africanist Paleolithic archaeologists remains: that the

MSA of Africa was the most likely origin of modern human complexity and symbolism,

traits which would have required cultural transmission and nucleation of social groups

(Wiessner, 1983; Yellen and Harpending, 1972). The work that has been done to this end

has been largely conducted within the confines of “Industries”, and with a focus on end

product form, particularly of projectile points and scrapers (Clark, 1988). Yet support of

these claims in the form of measured technological patterning across space remains

lacking.

4.1.3 The MSA: In Search of a Unifying Theoretical Framework

Robust conclusions about MSA cultural transmission have thus far been fleeting for several reasons. In order to adequately capture patterns in technology across a swathe of space as large as eastern Africa, it is necessary to outline one’s framework. The simplest and most common scheme used in MSA studies is to use a relative chronology of a sequence of different culture-historical units, such as Early and Later MSA. This allows for a clean and simple organization of technological patterns and is easily comprehensible by multiple analysts. Using a culture-historical framework, however, is problematic for many reasons.

First and most obvious, the eastern African MSA is poorly dated. Very few

sequences are securely dated in the Middle and Late Pleistocene. Thus, assignment of

technological pattern to a chronological timeline is spurious at best. Such interpretations

are not tied to the evidence available, but rather are more likely a product of the analysts’

attempt to make chronological sense out of variation from a unilineal bias. The ultimate

88 goal may be to understand behaviors on a timeline, but until more chronostratigraphic control is obtained for the eastern African MSA, such a discussion is not yet possible.

Secondly, epistemological issues arise with a unilineal chronological framework.

Describing behavioral change as a factor of time emphasizes that time itself was the driver of change. A simplified timeline obscures the possibility that multiple technologies may have been employed concurrently. Placing technological patterns into discrete temporal units in a unilineal scheme will ultimately lead to blurred lines, or “transitions” as they are often called. This is not to say that chronological context is not important; rather, it is possible to describe technology in terms of chronological context without feeding into the underlying, often hidden agenda, of placing behavior on a unilineal timeline.

It is necessary instead to start with the basic building blocks of technology, to understand how aspects of a toolkit work together as a system (i.e. the technological organization (Nelson, 1991)), and subsequently how those facets change and respond to varying stimuli. While the analysts who excavated MSA assemblages were focused largely on individual sites, layers, or units within those sites—and individual artifacts— researchers today are able to ‘stand on their shoulders’ and begin to see patterns in technology that transcended individual sites and were present across multiple localities, regardless of time. Before debating the causality of behavioral change, be it functional, raw material, landscape, or cultural, stone tool technology and its interworking parts and how they are related to cultural transmission must first be understood.

89 4.2 Previous Work: Current Theory on Cultural Transmission in Paleolithic Studies

In the broader light of Paleolithic archaeology, studies of cultural evolution trace their origins back to culture history schools of thought (e.g. Kulturkresilehre (Kluckhorn

1936); Americanist culture history (Willey et al 1956)). Trigger (2007) argues that culture historicism emerged during a time when geographic variation was beginning to be more recognized in the archaeological record and the normative definition of culture was the result of that early realization. The normative approach suggests that culture is any shared group of ideas or norms. Proponents of this approach argue that culture is reflected in material remains. The normative approach was espoused by culture-historians in the early 20th century by scholars like Rudolf Virchow and V. Gordon Childe, who

eventually brought culture historicism to Britain. As Childe (1929) wrote,

"We find certain types of remains – pots, implements, ornaments, burial rites,

house forms – constantly recurring together. Such a complex of regularly

associated traits we shall term a 'cultural group' or just a 'culture'. We assume that

such a complex is the material expression of what today would be called a

people."

In American archaeology, culture-history dominated archaeological thought until the

1960s with the rise of processualism, or the “New Archaeology”. In 1965 Lewis Binford refuted the normative approach of culture, and instead called for a more multivariate definition of culture. Binford, nearly espousing a systems theory approach (Flannery

(1972), stated that culture is a system composed of subsystems, and that archaeological variability represents variation in these subsystems which may vary independently of each other as the system as a whole functions or changes (Binford, 1965). Furthermore, in response to taxonomies of culture, Binford argued,

90 “…emphasis on shared traits in our system of classification results in masking differences and in lumping together phenomena which would be discrete under another taxonomic method.”

Binford (1965) argued that culture is multivariate and cannot be studied in terms of a single-variable, i.e. “the spatial-temporal transmission of ideas.” Following the rise of processualism, archaeologists tried to use archaeological theory to explain artifact variability with a focus on defining units of analysis. Carr (1995a; 1995b) explicitly discussed the link between artifact form and sociality, particularly style. Carr described how the processual agenda, which placed style and function as intellectually opposed concepts, prevented the development of middle-range approaches to material style.

Drawing on ethnographic literature and style theory, Carr ranked artifact attributes to three hierarchies: the decision sequence hierarchy, the production sequence hierarchy, and the visibility hierarchy. The decision hierarchy refers to the process of decisions that a producer will make before production even begins. The production sequence refers to the order by which the steps of production are made. Finally, the visibility hierarchy refers to the degree to which the attributes are visible to others both physically and socially. Thus, what Carr offered to the growing body of literature on archaeological theory and artifact variability is a focus on physical nature of technology, and explicit focus on nested hierarchies of decision making therein.

Another product of the processual agenda was an increasing reliance on ecology to solve problems of human behavior, particularly from a perspective of optimization through behavioral ecology. The scope of behavioral ecology (BE) modeling is vast, and over the past two decades behavioral ecological models studied various topics including

91 child foraging behavior, conservation biology, demographic transitions, domestication and agricultural origins, division of labor, and more (Winterhalder and Smith, 2000).

Behavioral ecological modeling is especially useful in the study of technological organization. As Nelson (1991) defines it, technological organization is defined as,

“…the selection and integration of strategies for making, using, transporting, and discarding tools and the materials needed for their manufacture and maintenance.” Thus, technological organization is uniquely suited for BE modeling due to its range of decision-making steps, each of which can be summarized as optimization problems.

Technological organization (TO) is quickly gaining traction in archaeology, and may even be considered a paradigm in the Kuhnian sense (Carr and Bradbury, 2011).

Nelson was the first to discuss the TO approach in 1991, influenced by the archaeological theory wars of the late 1980s and the rising influence of processualism. The crux of TO as described by Nelson is summarized as follows, “Technological strategies weigh social and economic concerns with respect to environmental conditions and are implemented through design and activity distribution” (Nelson, 1991:51). This framework defines

Nelson’s hierarchy by which her chapter is structured (Figure 4-1). Location in the hierarchy is determined by “distance from material implications” but she emphasizes that all levels of the hierarchy are necessary, despite the fact that many research projects focus on only one aspect.

Figure 4-1. Levels of analysis in research on technological organization (Nelson 1991:95)

93 4.2.1 Behavioral Approaches to Cultural Transmission (BACT): Theory, Obstacles, and

Applications

Tostevin (2012) aimed to incorporate middle range data (e.g. known knapping mechanisms) into the study of Paleolithic cultural transmission, describing it as a

“behavioral approach to cultural transmission” (BACT). Tostevin’s ideas were shaped by his interests in the Levantine Upper Paleolithic. Tostevin outlines flintknapping

experiments that tracked the observational behavior of knappers and observers.

Combining these data with those of other experiments, Tostevin argued that platform

characteristics, such as faceting, are more likely to be embedded in cultural transmission

chains than overall shape. Another aspect of tool production that knappers decide is the

convexity of the flaking surface. Therefore, Tostevin argues, attributes that reflect

convexity maintenance, such as curvature of flakes, or the presence of core edge

(débordant) flakes, also carry culturally transmitted information. Both of these groups of

attributes are tied to knapper behavior and move beyond the geometric morphometric

approach to quantifying end shape.

These different components of knapper behavior (platform preparation and

convexity maintenance) and the lithic attributes that reflect the decisions can be grouped

into discrete units, which Tostevin calls “domains”. He defines four discrete domains: 1)

Core modification, 2) Platform maintenance, 3) Direction of core exploitation, and 4)

Convexity maintenance. These four decision-based “domains” are conceptually separate

from the composition of the assemblage itself, which Tostevin calls “toolkit

morphology”. Toolkit morphology refers to the relative composition of the assemblage,

for example, the relative abundance of blades, points, or unretouched flakes. While

94 components of the toolkit were themselves byproducts of the four knapping domains described above, when analyzed together, toolkit morphology encodes a culturally transmitted behavior in itself, that may reflect the functional needs of the knapper(s).

The BACT approach is useful in that it creates measureable datasets, comprised of independent variables (see Tostevin 2012 for measures of independence), which can be compared across space and through time without a priori assumptions about toolkit relatedness. Some criticize the approach as not offering anything new. Indeed most lithic analysts already collect these kinds of data. The contribution of the BACT approach, however, is the analysis of the datasets. Consider the traditional shape-based comparative approach. If two assemblages are found to have similar tool types or shapes (e.g. Pinnacle

Point and Sibudu both having “Howieson’s Poort” backed blades) it may be argued that this represented a cultural connectedness (Mackay, et al., 2014). This approach ignores the possibility that the two groups may have independently created the tools, and the possibility that their similarity may reflect similar degrees of reduction (Hiscock, 2004).

If two assemblages are observed to share several of the “behaviorally-attuned” attributes outlined in BACT, the possibility that the similarities are the result of transfer of information is higher. While it is impossible to know with 100% certainty all of the multiple processes that formed archaeological patterns, the BACT approach enables analysts to systematically test the goodness of fit of competing models of technological change.

This kind of approach is sorely needed in African MSA lithic analysis, in which similarities across space (“techno-complexes”) are sometimes taken to represent culturally connected paleo-populations and in which innovations are often viewed in

95 terms of cognitive capabilities rather than evolutionary context. This dissertation builds on the work of Tostevin by experimentally testing the role of the BACT attributes in different forms of information transfer (Chapter 2).

4.3 Methods: BACT Analytical Methods

The flintknapping process was broken down into discrete domains according to

Tostevin. Some of the steps were omitted or altered to accommodate MSA datasets.

Domain 1: Core Modification

The first domain considered is related to core reduction strategy. Based on the results of Chapter 2, this domain is expected to be the most susceptible to being embedded in transmission chains.

Step 1: Core Orientation

Core orientation relates to how the knapper approached a nodule. Tostevin defined three variants in assemblages from European Middle and Upper Paleolithic sites: broad-faced, longitudinal, and discoidal. According to Tostevin these are the only categories that were represented and they represent discrete categories. Thus a first step in this analysis was to consider the “variants” present in the Nasera and East Turkana collections. This immediately creates problems, because Chapter 3 and other experiments have shown that core shapes grade into one another, and relying on final core form to determine orientation may miss earlier strategies that were erased by later flake scars. As such, this analysis aimed to differentiate broad patterns in reduction approach in a way so that each variant was non-overlapping and distinct, with the recognition that these units included large “shades of gray”. Based on results of Chapter 2, and Mehlman’s dissertation, the following variants were decided: bipolar, platform, and peripheral. In the

96 2015 dataset, peripheral abundance was calculated by combining discoidal, Levallois,

and any other cores with radial or centripetal flaking. Platform cores included all single-,

double-, and multiple- platform cores and ad hoc/migrating plane cores. Bipolar cores

included cores with diagnostic bipolar attributes such as opposed crushing.

Domain 2: Platform Maintenance

Platform Maintenance is the most well studied flintknapping domain in terms of middle range experiments (Dibble, 1997; Magnani, et al., 2014; Tostevin, 2012).

Platform preparation is carried out to guide conchoidal fracture through the flake, rather than exploding on impact, and usually involves trimming, faceting, and/or grinding. All of these serve to reinforce the striking area, possibly to absorb shock and prevent shattering or stepped and hinged flakes, although mechanical experiments are needed to prove or disprove this. Approaches to study platform preparation strategies in Africa are mostly derived from the patterns seen in Europe. More work is needed to document different forms of platform treatment in the African MSA. In this study, the platform maintenance domain was studied using two variables: platform preparation, platform thickness, and external platform angle.

Step 1: Platform Preparation

As described above, platform preparation can take the form of several, sometimes

overlapping methods, and thus can be manifest in many forms. Therefore in the Nasera

analysis, the assemblage was broken down into a simple scheme: prepared or unprepared.

In order to combine the 2015 and Mehlman datasets, the 2015 dataset was binned such

that any platform with any number of facets and or dorsal trimming, as evidenced by

small often stepped removals on the proximal end of flakes, was considered “prepared”.

97 Step 2: Platform Thickness (mm)

Platform Thickness (PT) is a linear measurement that directly corresponds to the

depth at which the knapper struck the edge of a core (Dibble, 1997; Pelcin, 1997).

Step 3: External Platform Angle (EPA, degrees)

External platform angle (EPA) is the angle of the dorsal surface relative to the platform. Many quartz flakes are such that EPA is difficult to measure and this affected sample size with the Nasera dataset and thus was omitted for that dataset.

Domain 3: Direction of Core Exploitation

Core exploitation refers to how the knapper removed flakes from the core. It is

different from core modification in that it refers to treatment of individual faces rather

than approach of the overall geometry. Using methods described in Chapter 2, number of direction changes was calculated for both early stage flakes and late stage flakes. Also technological flake category was used following Toth (1987).

4.3.2 Obstacles to BACT Approaches

One immediate concern with the BACT approach is the fact that, as detailed in

Appendix A, stone tool production is a reductive process, and shape changes as cobbles are further reduced. As such, decisions become more limited with each strike (Odell and

Henry, 1989). Additionally, stone artifacts were retouched, re-sharpened, and/or recycled.

More research, like that outlined in Chapter 2 and Appendix A, is needed to elucidate how the variables associated with cultural transmission change across the reduction sequence, or if these variables even maintain independence across the reduction sequence.

98 Furthermore, these processes of reduction create the “end product fallacy” as

described recently by Dibble et al. (2016), among others, in which the form of an artifact found by archaeologists likely differs from that which was manufactured, which itself differs from its state upon discard. Therefore, as Tostevin admits, the end states in which artifacts are excavated and analyzed may not adequately reflect the technological processes that formed them. This is particularly the case in the core orientation domain, in which the variants must be decided a priori. As such, the analytical protocol of BACT, particularly in relation to core form (e.g. platform, bipolar) is not yet divorced from typology and may obscure underlying variation. Methods like those outlined in Chapter 3 would alleviate this problem.

4.4 Application to the Archaeological Record: Nasera and East Turkana

A BACT approach to lithic variability in the eastern African MSA, in which the units of analysis and theoretical frameworks are explicitly defined, is sorely needed to begin to understand the role of sociality in human behavioral evolution. At Nasera, in northern Tanzania, Mehlman (1989) documented a sequence of defined industries that were sequentially replaced over time. Similar industrial sequences are also seen at the nearby sites of Mumba and Eyasi. However it is not yet clear to what extent the technologies between these sites are distinct, or if their perceived similarities are limited only to presence/absence of typological traits. Furthermore, it is unclear how the technology at Nasera changed through time. Mehlman (1989) meticulously documented these changes based primarily on toolkit morphology, but proxies that are associated with cultural transmission at Nasera have yet to be studied. Therefore applying a BACT

99 approach will situate technological change at Nasera in a way that can be tested against null models.

In Turkana, the BACT approach is applied across space at sites of known provenience which correspond to roughly the same stratigraphic interval, to determine the extent to which different environments and site formation processes affected technological patterns.

100 Chapter 5. Nasera Rock and the Middle to Late Stone Age Transition

5.1 Introduction

The Middle to Late Stone Age transition represents one of the most conspicuous

changes in the archaeological record of Africa (Tryon and Faith, 2016). It is associated

with the proliferation of ostrich eggshell(OES) beads and ochre use, and lithic technology

across this transition is characterized by the appearance of backed microliths, an increase

in bipolar knapping, and a general decrease in Levallois knapping methods (Ambrose,

2002; Eren, et al., 2013; Tryon and Faith, 2013). The timing and tempo of this transition

remains patchy. Enkapune ya Muto (EYM) provided early evidence for OES beads by 40

ka, but the EYM chronology has yet to be further elucidated given infinite radiocarbon

dates, and the fact that the technological patterns of the site are only summarized

(Ambrose, 1998; Ambrose, 2002). GvJm-22 at Lukenya Hill provided evidence that major shifts occurred by 50-26 ka, but the extent to which stratigraphic mixing occurred in the original excavations remains unclear (Tryon, et al., 2015a). New results from

Kisese II rock shelter in central Tanzania suggest the presence of LSA technologies by 40 ka, and major shifts at 35 ka, but these results stem mainly from unpublished field notes and severely biased assemblages from the original excavations (Inskeep, 1962; Tryon, et al., 2015b).

Nasera Rock in northern Tanzania is unique in that it provided one of the first sequences evidencing the chronological succession of the MSA-LSA transition in the region. L.S.B. Leakey first excavated the site in 1932, himself being influenced by recently published sequence from Magosi (Mehlman, 1989; Wayland and Burkitt, 1932).

Over forty years later, Michael Mehlman resumed excavations at Nasera, and documented that the shifts in lithic technology exhibited at Nasera were also documented

101 at nearby Mumba shelter and in the Eyasi basin (Mehlman, 1989). Northern Tanzania is therefore unique in that no other region of eastern Africa has documented archaeological evidence from multiple, contemporaneous localities suggesting similar changes in tool type frequencies over time. The Nasera sequence documents the shift from Levallois to bipolar flaking strategies in its lower levels, and the appearance of standardized backed microliths in its upper levels, trends that characterize the MSA-LSA transition.

Several models have been proposed to explain this transition. One model suggests that the MSA-LSA transition was the result of rapid behavioral development (Klein,

2009). If the revolution model is correct, it should manifest as an abrupt change in the cultural transmission patterns of the technological sequences, as MSA hominins were

‘replaced’ by LSA foragers (Klein, 2009). Little evidence from eastern Africa has supported this hypothesis, where technological change over time was mainly characterized as ‘gradual’ (McBrearty and Brooks, 2000; Tryon and Faith, 2013).

A second model suggests that the technologies in the LSA, particularly backed pieces, were developed as a means to reduce risk when environments where cooler, drier, and less predictable (Ambrose, 2002). If this second model is correct, there should be a correlation in shifts in toolkit morphology (sensu Tostevin 2012) with shifts in environment. Recent re-analysis of evidence from Nasera has supported this hypothesis

(Tryon and Faith, 2016). Tangential to the risk-reduction hypothesis is a hypothesis posed by Curtis Marean, here referred to as the territorial-cooperation hypothesis. Marean

(2016) proposes that the presence of predictable and high-quality resources led to the development of uniquely human forms of cooperation. He argues that dense, high-quality resources, such as shellfish beds, would have caused early Homo sapiens living 71 ka in

102 South Africa to become highly territorial, and such territorial behavior required

cooperation. In eastern Africa, Marean’s hypothesis could be tested by first modeling

when and where dense and predictable patches of resources were located, and

subsequently testing for standardization of lithic technologies surrounding those patches.

This kind of analysis requires a high-resolution record of faunal evolution for the MSA-

LSA transition that does not yet exist for eastern Africa. Current data suggests that, at

least for southern Africa, increasing human populations into the LSA resulted in

diminished large ungulate populations (Faith 2007). If foragers during the MSA-LSA

transition in eastern Africa emulated a seasonal grassland foraging strategy (sensu

Marean 1998), relying at least seasonally on ungulates, then ungulate density and

predictability would have been directly affected by increasing human population sizes.

Until a higher-resolution record of forager-fauna interactions is available for eastern

Africa, such as the distribution of smaller game in MSA-LSA assemblages, Marean’s territorial-cooperation hypothesis remains to be tested.

Finally, another model proposes that the MSA-LSA transition resulted from demographic changes in which populations became larger and denser, and more inter- connected (Mackay, et al., 2014; Powell, et al., 2009). If the demographic model is correct, and populations became more dense and inter-connected, it would have increased the potential for cultural transmission across unrelated groups. Heinrich (2010) argued that forager populations that are more connected are more likely to diffuse novel fitness- enhancing behaviors than weakly connected groups. An argument could therefore be made that increasing population density and inter-connectedness during the MSA-LSA transition resulted in a net increase in diversity of technology, particularly in aspects

103 known to be proxies for information transfer, like core reduction strategy (see Chapter 2

of this dissertation). Thus a tempting hypothesis is that diversity of core reduction

strategy increased with increasing population density at Nasera.

It is not yet clear, however, what effect increasing connectedness would have had

on forager lithic technological patterns. As Eerkens and Lipo (2005) have shown, most forms of transmission bias (e.g. conformist, prestige) actually serve to reduce diversity in technology. Mackay et al (2014), in studying technological change across later

Pleistocene southern Africa, laid out three expectations related to technological diversity

and information transfer, summarized as follows:

1. Diffusion of information through populations will result in sigmoid-shape

uptake curves, with slow initial uptake followed by rapid increase through to

saturation. If the technology is adaptively neutral it may subsequently decline

resulting in battleship curves (sensu Niemann 1995).

2. People in some areas will not be receptive to the uptake of new technologies,

even when they are adaptively beneficial, resulting in zones of non-uptake.

3. Information fidelity will decay with distance.

Mackay et al (2014) compared several high-resolution sites across the winter and

summer rainfall zones of southern Africa and concluded that human forager groups

fragmented and coalesced according to changes related to MIS. Coalescence piqued at

MIS 4 and MIS 2, and these assemblages were associated with increased ornamentation

and symbolic expression (Mackay et al 2014). Thus, the authors conclude, population

interaction was a primary driver in the innovation of these technologies (ibid). Flaking

104 systems were more dispersed inter-regionally during times of coalescence, and were

localized during times of fragmentation.

Based on Mackay et al, it is reasonable to expect that flaking strategies across the

MSA-LSA transition became more dispersed regionally as forager populations became denser. Unfortunately, such an inter-regional analysis is not yet possible for eastern

Africa. The current patchy state of the eastern African MSA-LSA record limits analyses to site-focused interpretations. At Mumba, for example, multiple excavations have produced different chronologies (Kohl Larsen 1938, Mehlman 1989, Prendergast et al

2007). Furthermore, large portions of the various Mumba assemblages are no longer located in eastern Africa, complicating systematic analyses. Future work should resolve this (Bretze and Conard 2017).

At this stage, study of the eastern African MSA-LSA transition remains, by and large, in its infancy. It is impossible to make a priori predictions about how technological patterns responded to stimuli from increasing population density from the perspective of a single site, such as Nasera. The best way to test this relationship is to first define proxies for population density, use those proxies to determine when population density increased at Nasera (Tryon and Faith, 2016), and subsequently determine how technological patterns, particularly core reduction strategy, corresponded.

To accomplish this, the BACT approach (Tostevin 2012) is useful in that it can elucidate shifts in technology at Nasera irrespective of previous industry designations. By controlling for raw material, and by including data on technological process like blank production, in addition to patterns of toolkit morphology, a more nuanced understanding of technological shifts over time is obtained. Furthermore, by building on previous

105 analyses of lithic technological change over time at Nasera that specifically examined

archaeological proxies for increasing human population density, the BACT approach can

be used to build a site-focused perspective on how flaking strategies, particularly in blank

production, changed as population density increased. In this way, a BACT application to

Nasera paves the way for future inter-site comparisons.

5.1.1 Nasera History of Research

L.S.B. Leakey first excavated Nasera, formerly known as Apis Rock, in 1932

with 10 trenches covering 100m2 of surface area. Mehlman later excavated Nasera from

1975-1976, during which some 75m2 of sediment were removed, yielding 283,000 lithics,

168,000 bone fragments, and 536 pottery sherds (Mehlman, 1989). A large portion of

these materials are still located at Leakey Camp at Olduvai Gorge. Leakey’s

archaeological materials are unavailable for study as their location is unknown, although

his field notes are available in their entirety in Mehlman’s PhD thesis. This study focuses on Mehlman’s collection described below.

Mehlman reached a maximum depth of 9m at Nasera, resulting in a complex stratigraphy which he described as consisting of 25 ‘levels’. Mehlman defined levels by a combination of natural strata and arbitrary spits. He subsequently combined several levels to form ‘distinctive sub-units’.

Of the 283,000 lithic artifacts recovered from the site, the majority were quartz, and Mehlman spent over a year painstakingly reviewing almost all of them. Personal accounts suggest that this time was destructive to Mehlman’s mental and physical health

(McBrearty, 2011). In addition to the 6-month excavation at Nasera, Mehlman also excavated at Mumba rock shelter and a third locality near Lake Eyasi. It was while

106 Mehlman was studying Nasera collections at Leakey Camp in 1981 that both of his

parents died within a week of each other. Unaware, he traveled to Nairobi for a respite, at

which point Sally McBrearty informed him of the untimely news. Mehlman quickly

traveled to the US, and never returned to eastern Africa (McBrearty, 2011). He finished his dissertation eight years later in 1989.

Several attempts have been made to date the Nasera sequence. First, Mehlman himself reported nine radiocarbon dates (Table 5-1) undertaken with Illinois State

Geology Survey as part of a study to determine the consistency of dating apatite relative to total organic matter. Thus he reported both values, and argues that those with considerable agreement in apatite and total organic matter are more reliable.

Table 5-1. Mehlman radiocarbon results (adapted from Mehlman 1989:45).

Level Industry Age (Apatite) Age (Organic) 3A PN/Akira ware 2,060 ± 100 2,180 ± 200 3A Olmoti/ Kansyore ware 5,400 ± 150 4,720 ± 105 3B Silale LSA 8,100 ± 120 7,100 ± 75 4 Lemuta LSA 18,280 ± 645

4 Lemuta LSA 22,460 ± 500 14,770 ± 205 5A Lemuta LSA 21,700 ± 600 21,600 ± 400 6 Nasera 18,475 ± 860

6 Nasera 22,350 ± 380 22,910 ± 400 7 Nasera 17,080 ± 130 20,360 ± 303

Additionally, Mehlman carried out uranium series dating with three samples

(Table 5-2). Amino acid racemization (AAR) was carried out on 13 samples (Table 5-3)

in conjunction with J. L. Bada Brooks on bone, but reliability of AAR on bone is

contested (Hare, 1988). Julie Kokis, in conjunction with Alison Brooks, later carried out

amino acid racemization on two samples from Layer 4 at Nasera (Kokis, 1998); Table 5-

107 4). Finally, in 2016, the author and Christian Tryon obtained 4 additional radiocarbon

samples from OES fragments (Table 5-5).

Table 5-2. Mehlman uranium series data (adapted from Mehlman 1989:46).

Level Lab# U ppm 238U 234U 232Th 230Th 230Th Date 3B 82-21 11.64±1.42 8.686±1.059 16.580±1.695 0.245±.042 1.393±.104 9,343 6 82-26 3.41±.04 2.541±.03 3.465±0.038 0.033±.003 0.738±.013 25,599 17 82-34 2.89±.07 2.159±.055 2.828±.067 0.067±.007 1.162±.033 55,960

Table 5-3. Amino acid racemization results from fossil bone (Mehlman 1989:46).

D/L Lateral Level Aspartic Date BP Provenience Acid 2 E3N2 SW 0.131 900 3A E2N4 W1/2 steps 0.212 * 3B W4N3 NE 0.548 30,000 4 E3N2 SW 0.406 20,000+ 5A E2N1 W1/2 0.428 ** 6 E3N1 W1/2 0.486 26,000 8/9 top E3N1 W1/2 0.355 17,000 8/9 E3N1 W1/2 0.41 20,000 12 E2N3 SE 0.496 26,000 15 E2N2 SW 0.516 28,000 16 E2N3 SW 0.52 28,000 17 E2N3 SW 0.504 27,000 17B W1N3 SE 0.469 24,000 -5 -1 *Holocene kasp=6.7 x 10 yr , based on ISGS-438 date (organic fraction) from level 3A -5 -1 ** Pleistocene kasp=1.8 x 10 yr , based on ISGS-445 date (organic fraction) level 5A + Date erroneously published as 22,000 bp in Bada (1981:284).

Table 5-4. Nasera amino acid ephimerization results from Kokis (2008).

Level A/I Ratio A/I Age 4 0.59 44,000 4 0.45 32,500

108

Table 5-5. New radiocarbon dates by Tryon and Ranhorn (unpublished).

UBA No. Sample Level Material 14C ± F14C ± ID UBA- 44 7 Ostrich >50,12 32352 eggshell 2 UBA- 54 5 Ostrich >50,12 32353 eggshell 2 UBA- 4 5B+6 Ostrich >46,00 32354 eggshell 9 UBA- 20 3B/5 Ostrich 10,013 5 0.287 0.00 32355 contact eggshell 5 5 2 UBA- 40 5A Ostrich >50,12 32356 eggshell 2

There are many inconsistencies among the five chronometric datasets at Nasera.

For example, in Level 3B Mehlman’s collaborators conducted an absolute radiocarbon

test in which the sample was reportedly split into two pieces, and one of the pieces was

crushed and boiled in NaOH to remove contaminants, and both returned the same result

of 8,100±120 B.P. (USGS-427), which they considered strongly reliable. Thus when a

uranium series sample from level 3B returned a date of 9,300 years, it was assessed as

contaminated and was discarded as unreliable. A racemization date for this level returned

30,000 years, which Mehlman argued, “undoubtedly results from analyzing a bone

fragment from subjacent deposits (Levels 5-7)” (Mehlman 1989:44).

Overall, the ISGS radiocarbon results reported by Mehlman appear stratigraphically consistent, and were no doubt integral in framing his industry designations. His originally proposed sequence dated from ~2 ka in the Pastoral Neolithic and increased gradually with depth to ~17-22 ka in Levels 4/5 and 6/7 with considerable vertical mixing among the 4 Levels. The maximum ISGS 14C date obtained by Mehlman

came from Level 4 dated to ~22 ka, and no radiocarbon dates were reported beyond

109 Level 7. Both amino acid and U-Th data returned similar dates for Level 6 of ~26 ka, which Mehlman deemed adequate, however the amino acid results directly below this in

Levels 8/9-17 returned dates ranging from 20-28 ka. It is possible that Levels 4/5 and 6/7 represent a palimpsest of reworked deposits dating ~17-22 ka, based on 14C results, and if the amino acid results are correct, then it is possible that the underlying layers represent a slightly older interval, with Levels 12-17 dating to ~26-28 ka.

Newer lines of evidence suggest an older age for Nasera starting in Level 4.

Results from Kokis (1998) placed Level 4 between 44 and 32.5 ka. OES radiocarbon is more reliable than bone radiocarbon in tropic conditions particularly in the absence of pre-treatment methods. Results of the OES radiocarbon samples suggest that everything below Level 5 is older than 45 ka. More analyses of these OES fragments are needed to rule out mixing and possible burning. Finally, one rhinoceros tooth from Spit 17 was dated with uranium series to ~56 ka, suggesting to Mehlman that this part of the sequence should be considered Middle Stone Age (Kisele Industry).

Mehlman’s 756-page dissertation is one of the most comprehensive accounts of the MSA and LSA of eastern Africa. Despite the usual ambiguities that characterize lithic technological studies, particularly regarding industrial designations, the main result of

Mehlman’s tireless efforts is two-fold: 1) Human technology in northern Tanzania during the Late Pleistocene was characterized by both time-successive patterns of tool type frequencies that were shared across space and, 2) The technological attributes by which these patterns are defined changed gradually over time.

110

Figure 5-1. Plan view of Nasera Rock showing Leakey (dotted line) and Mehlman (solid line) excavations. From Mehlman 1989.

111

Figure 5-2. Nasera stratigraphic profile (from Mehlman 1989).

112

Figure 5-3 Grid plan of Mehlman’s excavations. From Mehlman 1989 and (Mehlman, 1977).

5.2 Nasera analytical setup

The Nasera dataset was analyzed using stratigraphically defined units (Table 5-6).

These stratigraphic aggregates defined by Mehlman (1989) follow geological boundaries

of the sequence and are not defined by any archaeological data. Additionally, Mehlman

used technological patterns of artifacts to propose lithic industries (Kisele, Mumba,

Nasera, Olmota) which, he argues, comprise the lithic industrial sequence that spans

northern Tanzania sites of Nasera, Mumba and Eyasi. Unit IV in this analysis

corresponds to Levels 18-25. Unit III corresponds to Level 12-17, and Unit II to Levels

8/9-11. Finally, Unit I consists of Levels 6 and 7. By using the BACT approach applied

113 to discrete geological units, this analysis will test Mehlman’s model of change for

Nasera. It is expected that Units IV and III (both Kisele according to Mehlman) will exhibit continuity and have fewer differences in the lithic attributes across this span.

Based on Mehlman’s industries, it is expected that there will be differences between

Units III and II which represent stratigraphic aggregates associated with the Kisele and

Mumba industries, respectively, and also between Units II and I which represent the

Mumba and Nasera industries.

Blank production and toolkit morphology were measured as outlined in Tostevin

(2012) and in Chapter 4. To accomplish this, two datasets were used: the 2015 dataset obtained by the analyst was the primary dataset. When possible, additional data were mined from Mehlman’s published thesis to increase sample size and robusticity of analyses.

Table 5-6. Stratigraphic units used in Nasera BACT analysis.

Unit Strata Industry (Mehlman 1989) IV 18-25 Kisele III 12-17 Kisele II 8/9-11 Mumba I 6 & 7 Nasera

5.3 Composition of the Nasera Dataset

Of the 280,000 lithics recorded by Mehlman, ~15,000 are estimated to be present in the Nasera collection in the Leakey Storehouse at Mary Leakey’s Camp at Olduvai

Gorge today. The Nasera collection includes artifacts, fauna, and other cultural remains such as OES beads and ochre. The collection represents four trenches: CE (central excavation), WCE (west central excavation), NST (North South Trench) and EWT (East

114 West Trench). The excavation extended over 6 meters in depth in CE resulting in 25

“Levels”. The collection was studied by previous researchers other than Mehlman,

including Prendergast (2007) and Bushozi (Bittner et al 2007). The current state of

organization is compromised in many ways and it is not clear how the original collection

was organized. The collection is organized roughly by square and level, information that

is most still preserved on most, but not all, artifact bags.

The Nasera re-analysis study required the author to re-curate the entire

assemblage, which was previously stored in metal jerry cans. Throughout analysis, a

Maasai student (William Olemoita) was recruited to help write new cards and provide

new bags to replace the dilapidated storage material of the assemblage. After analysis of

a jerry can was complete, the artifacts were returned to new bags with re-written cards and were placed in new trays, and corresponding labels were placed on the front of each tray.

115

Figure 5-4. The Nasera collection upon arrival (left) and after curation (right). Throughout this process, all pieces were laid out and examined qualitatively, albeit

quickly, and complete flakes and cores were pulled for measurement. Throughout this

process it became clear that of the 26 jerry cans located at Leakey Camp, each of which

was divided further into larger bags, most were labeled “angular waste”, “rolled”, or

“rubble”. Only one box labeled “Nasera Tools” is present at Leakey Camp. Mehlman

illustrated and described hundreds of retouched pieces and cores. Some of these pieces

were shipped to the United States and Germany for further study. However it is highly

unlikely that the remainder of the assemblage—some 265,000 pieces—was shipped elsewhere, as this would have been very logistically difficult. Extensive research and communication with the Department of Antiquities, National Museum, professors at the

University of Dar es Salaam, and former colleagues of Mehlman provided no answers as to the whereabouts of the remainder of the collection. Thus this analysis resorted to

116 studying mostly angular waste in an attempt to glean general core reduction strategies

through time at Nasera. In addition to qualitative study of all the pieces, 265 lithics were

directly measured and entered into the dataset (Table 5-7).

Figure 5-5. Examples of deteriorating state of Nasera assemblage.

117

Figure 5-6. Missing tools in the Nasera assemblage. Mehlman reported 92 total points in the Nasera assemblage but only a few are still housed in the Leakey Camp collection.

Table 5-7. Nasera Measured Lithic Dataset.

Industry Blade Complete Core Flake Hammer Retouched Grand Blade Flake Frag Manuport Piece Total Frag Grindstone Kisele 5 27 14 36 6 12 100 Mumba 3 14 4 5 1 27 Nasera 5 45 30 19 2 34 135 Total 13 86 49 60 8 48 264

5.3.1 Initial Lithic Analysis Results

Prior to the BACT analysis, the assemblage was studied according to a comprehensive coding scheme (following Wilkins et al 2017). This analysis served to determine the integrity of the assemblage, the relative raw material composition, and general patterns of technology (e.g. qualitative study of core reduction strategies).

118 Despite the assemblage being largely compromised, Levallois reduction was visible in convergent distal fragments and faceted platforms. For example, both basalt and chert convergent flake fragments were recorded, and some of these distal point fragments had visible diagnostic impact fractures, mainly step-terminating bending fractures. Levallois cores were also recorded on all raw materials. Proximal flake fragments exhibited platform preparation in the form of faceting and dorsal trimming.

This interval was also characterized by some bipolar reduction, particularly as a means to split pebbles, followed by centripetal removal of flakes. This pattern of reduction has also been observed at Kisese II by the author, as well as in the Democratic Republic of

Congro (Cornelissen, 2016), and was referred to by Nelson (1973) as semi-radial pebble cores. Several large stones were also observed in this unit, with evidence of both pitting from use as an anvil, and also battering from use as a hammerstone. There were several occurrences in which observed flakes and cores appeared to belong to the same “raw material unit” (RMU) as defined by Conard and Adler (1997). RMU was determined using cortex, color, homogeneity of grain size, inclusions, and texture. Re-fitting analyses were not possible due to the heavy bias of the studied assemblage. However the mere presence of the RMU suggests that the in situ material was minimally disturbed post- depositionally and possibly reflects individual knapping events rather than severely time- averaged palimpsests.

Levels 7, 8, 9, 10, and 11 were stored together and often labeled as one unit, thus these pieces were studied together. Again these bags mainly represented angular waste and rolled rubble. This level appeared to show an increase in raw material diversity relative to the lower levels, particularly with higher amounts of obsidian and basalt. This

119 observation was not confirmed by Mehlman’s results, in which chert and ‘other’ comprised 16.4% of the relative assemblage of major artifact classes in Levels 8/9-11,

19.3% in Levels 12-17, and 16.4% in Levels 18-25 (Mehlman 1989). There is actually a marked decrease in raw material diversity, based on Mehlman’s results, with chert and

‘other’ materials comprising only 5.2% of the total major artifact classes in Levels 6+7.

Thus the perceived increase in raw material diversity seen in Levels 7, 8, 9, 10, and 11 is probably due to an incomplete analyses of prior and later levels.

There also appeared to be a higher degree of rolled artifacts in this level, but this may simply be because the rolled material is what remains at Leakey Camp and potentially fresher pieces, like the ones described in Mehlman’s dissertation, are stored elsewhere. Quartz shatter included pieces < 2cm, indicating minimal post-depositional water transport (Schick, 1987) or collection bias. Some retouched fragments were recorded in this level, especially on chert pieces. Overall, quartz was worked primarily with bipolar, and bipolar splinter cores were very common in these levels. Finally, possible evidence for fire modification of artifacts was observed in the form of color alteration of chert (translucent to bright white) as well as potlid fractures on other pieces.

Given the presence of burned OES beads in these levels, it is reasonable to suspect potential hearths in these levels. However the only hearths Mehlman described occurred at Mumba, and Leakey’s own field notes from the Nasera excavation specifically state a lack of evidence of hearths. It may be possible that the artifacts were heat treated intentionally, but more analysis is needed to confirm this.

Figure 5-7 shows raw material composition through time at Nasera, as compiled from Mehlman’s data. This figure exhibits only tools and cores. Debitage was removed

120 from this analysis to prevent false inflation of quartz due the high amounts of shatter produced during quartz knapping (Tallavaara, et al., 2010). to This figure demonstrates a clear trend toward decreasing levels of chert and increased levels of quartz throughout the sequence. Figure 5-8 shows core orientation through time as described in Mehlman 1989.

This in combination with Figure 5-7 shows that core reduction strategy may track raw material at Nasera, with levels higher in quartz composition exhibiting more abundance of platform and bipolar strategies, and levels with more chert exhibiting a focus on peripheral flaking strategies (i.e. centripetal/discoid and Levallois) (χ2 = 212, df =24 , p <

0.001).

100% 90% 80% 70% Other 60% 50% Chert 40% Quartzite 30% Quartz 20% 10% 0% 18-25 12-17 8/9/2011 6/7 4/5

Figure 5-7. Raw material composition through time (from Mehlman 1989).

121 100% 90% 80% 70%

60% %Amorphous 50% %Bipolar 40% %Platform %Peripheral 30% 20% 10% 0% 18-25 12-17 8/9-11 6/7 4/5

Figure 5-8. Core orientation through time at Nasera (from Mehlman 1989). In summary the most striking aspect of the Nasera assemblage that arose from the preliminary lithic analysis was the differential approach in technology to different raw materials. Unsurprisingly, quartz was predominantly worked with bipolar, whereas chert comprised complete flakes from free hand percussion and was more commonly flaked centripetally from one or two faces.

5.4 Nasera BACT Results

5.4.1 Blank Production

Core Modification

Core orientation was analyzed using two datasets: the 2015 dataset described above, and a combined dataset that incorporated data from Mehlman’s dissertation. The extent to which this later analysis was possible was dependent on the organization of

Mehlman’s data. For example, platform treatment, flake shape, and core shape data were

122 available in Mehlman’s thesis, but data regarding cortex, and flake scar directionality were unavailable.

Both analyses showed a significant difference in percent composition of core orientation between Units II and III. In both instances this significant difference reflects a decrease in peripheral flaking in Unit II relative to Unit III. The Mehlman dataset also exhibited a significant difference in percent composition of core orientation between

Units III and IV (p = 0.04, Fisher’s Exact Test) but this pattern was not significant in the combined dataset (p = 0.12). Both analyses revealed a higher abundance of peripheral flaking in Unit IV, with little bipolar and little platform approaches relative to Unit III.

Table 5-8. Differences in blank production at Nasera through time focusing on Domain 1: Core Modification.

Unit IV Unit III Unit II Unit I Flintknapping Steps by Domain 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera Domain 1: Core Modification

Core Orientation† %Peripheral 81% 57% 24% 23% %Platform 4.30% 0% 20% 21% %Bipolar 15% 43% 56% 56% n 69 14 25 541 p - 0.04 0.05 1.00 Core Orientation* %Peripheral 81% 60% 23% 24% %Platform 4.10% 0% 23% 21% %Bipolar 15% 40% 53% 55% n 73 16 30 567 p - 0.12 0.02 0.94

123

120

100

80 %Amorphous 60 %Bipolar %Platform 40 %Peripheral

0 4 5 6 7 8/9-11 12-17 18-25

Figure 5-9. Core orientation through time at Nasera.

Platform Maintenance

Platform maintenance was analyzed at Nasera according to platform treatment

and platform thickness. When only the 2015 dataset was studied, there was a significant

difference between Unit II and III. However, in the combined Mehlman-2015 dataset, the largest difference was observed between units III and IV. This difference is possibly explained by the biased nature of the 2015 dataset, which excluded tools.

Sample sizes for external platform angle were too small to conduct statistical tests.

Table 5-9. Platform maintenance at Nasera.

Unit IV Unit III Unit II Unit I Flintknapping Steps by 18-25 12-17 8/9-11 6 + 7 Domain Kisele Mumba Nasera Domain 2: Platform Maintenance Platform Treatment Unprepared 82.35% 100% 60% 68%

124 Prepared 18% 0% 40% 32% n 17 12 10 38 p - 0.25 0.03 0.7118 Platform Treatment* Unprepared 50.49% 72% 67% 57% Prepared 49.51% 28% 24% 43% n 103 29 61 111 p 0.06 0.8079 0.1957

The biggest different in platform thickness was observed between Units II and III

(p = 0.05, Fisher’s Exact Test). This reflects an overall decrease in platform thickness in both Units II and I.

Table 5-10. Platform thickness at Nasera. Flintknapping Steps by Domain Unit IV Unit III Unit II Unit I 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera Domain 2: Platform Maintenance Platform Thickness mean 7.27 7.11 4.65 5.75 standard deviation 2.83 2.99 2.77 2.40 n 22 13 11 44 p - 0.88 0.05 0.25 t - 0.16 2.09 -1.21 df - 24.17 21.80 14.00

Direction of Core Exploitation

Direction of Core Exploitation was measured following (Tostevin 2012) analyzing early and late exploitation separately. Variables used here to measure exploitation were number of direction changes (normalized by the flake area) and technological flake category (following Toth 1987). However, both normalized number of directions and the technological flake category are obscured on quartz flakes, and many flakes in this sample were classified as ‘unidentifiable’, leading to a low sample

125 size which affected statistical analyses (Table 5-11). Furthermore, data related to early and late stage core exploitation were not available in Mehlman’s thesis. Statistically significant differences were observed between Unit I and Unit II for early number of directions (p = 0.02, t = 2.70, df = 12.77) and also early technological flake category (p =

0.04, Fisher’s Exact Test).

126 Table 5-11. Nasera direction of core exploitation.

Flintknapping Steps by Domain Unit IV Unit III Unit II Unit I 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera

Domain 3: Direction of Core Exploitation Early Number of Directions mean 1.13 0.00 2.17 1.07 standard deviation 1.36 NA 0.75 1.03 n 8 1 6 15 p - - - 0.02 t - - - 2.7035 df - - - 12.777 Late Number of Directions mean 2.8 3 2.5 2.25 standard deviation 0.447 NA 1.732 1.409 n 5 1 4 20 p - - - 0.80 t - - - 0.27 df - - - 3.84

Early Technological Flake Category II 0% 0% 0% 20% III 0% 0% 17% 0% V 43% 100% 0% 40% VI 57% 0% 83% 40% n 8 1 6 15 p 1.00 0.29 0.04 Late Technological Flake Category II 0% 0% 0% 0% III 0% 0% 0% 16% V 20% 0% 0% 5% VI 80% 100% 100% 79% n 5 1 4 19 p 1.00 1.00 1.00

Dorsal Surface Convexity

Dorsal surface convexity was studied using two linear ratios of core measurements: breadth/length ratio and thickness/breadth ratio (Table 5-12). These analyses utilized a combined 2015 and Mehlman dataset. Cores in Unit I were broader relative to length compared to Unit II, and this difference was significant (p < 0.01,

Mann-Whitney U = 1589.) A non-significant difference was observed between Units III and II (p = 0.06, Mann-Whitney U = 95). Cores in Unit III were thicker relative to

127 breadth in comparison to Unit IV, and this difference was significant (p < 0.01, Mann-

Whitney U = 1018). No other differences were observed in core thickness/breadth ratio.

Table 5-12. Nasera dorsal surface convexity. Flintknapping Steps by Domain Unit IV Unit III Unit II Unit I 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera Domain 4: Dorsal Surface Convexity Breadth/Length mean 0.87 0.87 0.85 0.92 standard deviation 0.09 0.10 0.13 0.18 n 77 19 16 139 p - 0.41 0.06 < 0.01 W - 642.00 95.00 1589.00 Thickness/Breadth mean 0.64 0.70 0.71 0.67 standard deviation 0.16 0.17 0.17 0.15 n 77 19 16 139 p < 0.01 0.42 0.56 W 1018.00 127.00 1013.00

5.4.2 Toolkit Morphology

Toolkit morphology was measured with six variables: elongation index

(length/width ratio) of detached pieces, width/thickness ratio of detached pieces, scraper shape, distal termination, platform morphology (platform thickness/platform width), and tool type composition (relative proportions of backed pieces, small convex scrapers, and retouched points) (Table 5-13). Elongation index was analyzed using a combined 2015 and Mehlman dataset. The only significant difference in elongation index was observed between Units II and I (p < 0.01). Width/thickness ratio, distal termination, and platform morphology were all analyzed exclusively with the 2015 dataset, as relevant data was not available in Mehlman’s reported results. No statistical differences were seen across any of the units for any of these variables. Scraper shape was analyzed using data from

Mehlman’s reported results (Table I-4, 1989:656). No significant differences were found

128 in scraper shape across the four units. Finally, following Tostevin (2012), toolkit

morphology was analyzed using overall tool type relative composition. Because few tools

were available for study in 2015, this analysis relies on Mehlman’s dataset. All three

units showed a significant difference in tool type composition (p < 0.001) according to

Fisher’s Exact Test. These significant differences reflect the general decrease in retouched points, which were more abundant in lower levels, and a general increase in backed pieces and small scrapers in the higher levels.

129 Table 5-13. Toolkit morphology differences at Nasera.

Toolkit Morphology Variable Unit IV Unit III Unit II Unit I 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera Length/Width Ratio* mean 1.16 1.17 1.49 1.41 standard deviation 0.54 0.47 2.15 0.32 n 276 51 119 214 p - 0.74 0.19 < 0.01 W 6834 2648 1556 Width/Thickness Ratio mean 2.85 2.66 3.17 2.90 standard deviation 0.83 0.57 0.52 0.75 n 13 5.00 8.00 38.00 p 0.78 0.22 0.55 W 36.00 11.00 179 Scraper Shape Convex 49.6% 54.5% 63.2% 66.0% Straight 19.5% 0.0% 21.1% 12.8% Concave 12.2% 27.3% 5.3% 4.3% Irregular 18.7% 18.2% 10.5% 17.0% n 123 11 19 47 p - 0.24 0.17 0.84 Distal Termination Feather 46.2 100 55.5 86.7 HingeOrStep 53.8 0 44.5 13.3 n 13 4 9 30 p - 0.1 0.23 0.06 Platform Morphology mean 0.42 0.42 0.42 0.44 standard deviation 0.16 0.11 0.13 0.16 n 16 8 11 37 p 0.61 0.84 0.74 W 55 47 189 Tool Type %SmallConvexScrapers 1.60 0.00 6.52 5.92 %Backed 1.10 0.00 6.50 3.90 %Points 13.30 18.00 4.30 14.60 n Total Tools 188 61 46 355 p 0.09 < 0.001 0.06 Number of Differences / Steps 0/6 1/6 1/6 Total Difference: Unit IV vs. III 0 Total Difference: Unit III vs II 0.17 Total Difference: Unit II vs I 0.17

130 Table 5-14. Differences in Blank Production at Nasera through time.

Flintknapping Steps by Domain Unit IV Unit III Unit II Unit I 18-25 12-17 8/9-11 6 + 7 Kisele Mumba Nasera Domain 1: Core Modification Core Orientation† %Peripheral 81% 57% 24% 23% %Platform 4.30% 0% 20% 21% %Bipolar 15% 43% 56% 56% n 69 14 25 541 p - 0.04 0.05 1.00 Core Orientation* %Peripheral 81% 60% 23% 24% %Platform 4.10% 0% 23% 21% %Bipolar 15% 40% 53% 55% n 73 16 30 567 p - 0.12 0.02 0.94 Number of differences / steps 1 1 0 Domain 2: Platform Maintenance Platform Treatment Unprepared 82.35% 100% 60% 68% Prepared 18% 0% 40% 32% n 17 12 10 38 p - 0.2463 0.03 0.71 Platform Treatment* Unprepared 50.49% 72% 67% 57% Prepared 49.51% 28% 24% 43% n 103 29 61 111 p 0.06 0.8079 0.20 External Platform Angle (degrees) mean 81.55 89 85.71 85.23 standard deviation 7.78 NA 2.63 4.47 n 9 1 7 26 p - - - 0.72 t - - - 0.36 df - - - 16.60 Platform Thickness mean 7.27 7.11 4.65 5.75 standard deviation 2.83 2.99 2.77 2.40 n 22 13 11 44 p 0.88 0.05 0.25 t 0.16 2.09 -1.21 df 24.17 21.8 14.00 Number of differences / steps 0.33 0.67 0 Domain 3: Direction of Core Exploitation Early Number of Directions mean 1.13 0.00 2.17 1.07 standard deviation 1.36 NA 0.75 1.03 n 8 1 6 15 p - - - 0.02 t - - - 2.70 df - - - 12.78 Late Number of Directions mean 2.8 3 2.5 2.25 standard deviation 0.45 NA 1.73 1.41 n 5 1 4 20 p - - - 0.80 t - - - 0.27

131 df - - - 3.84 Early Technological Flake Category II 0% 0% 0% 20% III 0% 0% 17% 0% V 43% 100% 0% 40% VI 57% 0% 83% 40% n 8 1 6 15 p 1.00 0.29 0.04 Late Technological Flake Category II 0% 0% 0% 0% III 0% 0% 0% 16% V 20% 0% 0% 5% VI 80% 100% 100% 79% n 5 1 4 19 p 1.00 1.00 1.00 Number of Differences / steps 0 0 0.5 Domain 4: Dorsal Surface Convexity Breadth/Length mean 0.87 0.87 0.85 0.92 standard deviation 0.09 0.10 0.13 0.18 n 77 19 16 139 p - 0.41 0.06 0.01 W - 642.00 95.00 1589.00 Thickness/Breadth mean 0.64 0.70 0.71 0.67 standard deviation 0.16 0.17 0.17 0.15 n 77 19 16 139 p 0.01 0.42 0.56 W 1018.00 127.00 1013.00 Number of Differences / steps 0.5 0 0.50 Total Difference: Unit IV vs. III 1.83 1 Total Difference: Unit III vs II 1.67 Total Difference: Unit II vs I 1

5.5 Discussion

5.5.1 Differences in Blank Production at Nasera

Overall differences in blank production were visualized following Tostevin

(2012) in which the significant differences of each flintknapping step were first totaled within the domain and weighted accordingly by dividing the number of differences by the total number of steps in the domain (Table 5-14). In cases where analyses were carried out twice (e.g. in core orientation with the 2015 and combined 2015/Mehlman dataset) the differences were weighted as only one step. Next, the total number of weighted

132 differences across the four domains were totaled to provide a total difference of blank

production between units of analysis.

According to this scheme, the core orientation domain resulted in a difference of 1

(1/1) for the transition from Unit II to Unit I and the transition from Unit III to Unit II.

Core orientation was studied with the following variants: bipolar, peripheral, and platform. One issue that arises with this scheme is that bipolar knapping refers to a technological strategy, whereas peripheral and platform refer to geometric configuration.

Qualitative analysis of the Nasera assemblage suggest that knappers opened cobbles or pebbles using bipolar methods, and then continued flaking the piece centripetally. The use of multiple core reduction methods in a single lithic reduction highlights the importance of studying patterns of technological process rather than form. This analysis does not sufficiently capture this variation largely because sample sizes were too small and because the methods were not attuned to quartz.

Domain 2 (platform maintenance) exhibited a weighted difference of 0.33 (1/3) for the transition from Unit IV to Unit III, a weighted difference of 0.67 (2/3) for the transition from Unit III to Unit II, and 0 for the transition from Unit I to Unit II. This difference in the lower levels could be explain by a shift toward increasing bipolar flaking by Level 12-17 (Unit III) and an even more pronounced increase in bipolar flaking by Level 8/9-11 (Unit II) (Figure 5-7).

Domain 3 (direction of core exploitation) exhibited a weighted difference of 0 between the earlier two transitions, and a weighted difference of 0.5 for the transition

from Unit II to Unit I. This pattern was almost certainly driven by extremely low sample size for the earlier levels. This low sample size stemmed from the difficulty of coding

133 technological flake category and flake directionality on most quartz flakes. New proxies

for early and late core exploitation that are explicitly attuned to the unique flaking

patterns of quartz are needed before further conclusions can be drawn.

Domain 4 (dorsal surface convexity) was measured using shape ratios of cores

provided in Mehlman’s thesis. A weighted difference of 0.5 was exhibited between the

transition from Unit IV and Unit III, and between Units II and I. This correlates to a trend

towards cores that a broader relative to length in the uppermost levels analyzed (Unit I).

Cores showed a slight variation toward increasing thickness relative to width in the

middle levels Units II and III in comparison to the early and later levels. These slight

variations, which included only quartz, could be attributed to baseline variation in quartz reduction, possibly from copy errors (sensu Eerkens and Lipo 2005). It is also possible that shape ratios like width/length and thickness/width do not adequately capture variation in dorsal surface convexity on quartz cores. A bipolar split semi-radial core could feasibly exhibit similar ratios to a bipolar core despite resulting from completely different technological processes. More nuanced quantitative measures of dorsal surface convexity, such as those outlined in Chapter 3 of this dissertation were not applicable to the quartz cores at the time of study. This is because the diminutive nature of quartz cores, coupled with its glossy surface, made 3D capture with photogrammetry difficult.

Efforts to rectify these issues are ongoing.

In terms of blank production, no abrupt shifts were observed through time.

Rather, differences gradually accumulated across the three transitional units (with total weighted differences of 1.83, 1.67, and 1 respectively). The most pronounced shift at

134 Nasera occurred between Units III and II (weighted difference 1.83). This transition

corresponds to the transition between Mehlman’s Mumba and Kisele industries.

This shift is characterized by a significant decrease in peripheral flaking between

Levels 18-25 and Levels 12-17. However this shift is not necessarily correlated to raw

material; Levels 12-17 exhibited more chert than Levels 18-25 and yet was characterized

by less peripheral flaking. Given the expectation that finer grained raw materials are more

likely to be reduced with peripheral (e.g. Levallois) flaking methods, and quartz more

likely to be reduced with bipolar or platform strategies (Tallavaara, et al., 2010), this

result is surprising. It is possible that the finer grained raw materials were instead used for

another reduction strategy requiring fine knapping control, like bladelet production, but

evidence for this was not observed until later in the sequence.

5.5.2 Differences in Toolkit Morphology at Nasera through Time

Toolkit morphology was visualized following Tostevin (2012) in which all toolkit morphology variables were totaled together. This is because the nested knapping decisions that represent Tostevin’s domains of blank production are not readily present in toolkit morphology. An argument could be made that the forager toolkit was divided into different functional compartments, but applying this to a lithic analysis would require explicit understanding of the functional use of each tool type, which is as yet unknown.

As such the comparisons made here totaled all differences in toolkit morphology without prior weighting.

Overall very few differences were seen in the toolkit morphological variables.

One significant difference was observed in the elongation index of detached pieces (flake

135 length/flake width) between Units I and II (p = 0.01, Mann-Whitney U = 1556) which

may reflect an increased focus toward the production of blade/bladelets.

In terms of tool type composition, a significant difference was only observed

between Units III and II (p < 0.001, Fisher’s Exact Test). Given the typological nature of

this variable, and the unavailability of these pieces for study, this observation should be

taken with caution. The presence/absence of retouched points appears to be driving the

changes across the sequence studied here. However, the results do not suggest a gradual

trend of decreasing retouched points from the earlier Units (IV and III) to the later Units

(II and I), as one would expect in studying the MSA-LSA transition. Rather, retouched

points decreased only in Unit II, and then increased to 14.6% of relative tool proportion

in Unit I (Levels 6+7, Nasera Industry). The significant difference between Unit II and III

is likely driven primarily by this difference in retouched points, which account for only

4.3% of the assemblage in Unit II (Levels 8/9-11, Mumba Industry). Both Units II and I exhibited relative increases in proportion of backed pieces (6.5% and 3% respectively) and small convex scrapers (~6% in both). Given the antiquity of new radiocarbon dates, which suggest that Levels 4 and below are > 45 ka, this pattern of toolkit morphology makes sense. The relative decrease in retouched points in Unit II could be explained by a functional variable. According to Mehlman’s data, retouched points increase again in

Unit I and do not fully disappear until Levels 4/5, which were not included in this analysis. Furthermore, this would suggest an early appearance for backed blades and small convex scrapers, which is in alignment with records elsewhere in Africa (e.g.

Aduma, Pinnacle Point).

136 5.5.3 BACT in the MSA: Lessons Learned

Applying BACT to the Nasera sequence has provided several lines of insight.

First, it is clear that the results of the BACT approach are highly determined by the

analysts’ units of analysis. Previous BACT studies employ stratigraphic designations as

independent units of analysis that can be compared through time and across space.

Therefore BACT units of analysis are essentially sedimentological packages, completely

at the whim of geological processes. This is important because lumping together, as done

here, Level 18-25 to represent Unit IV may actually be averaging a time period orders of

magnitude larger than another Unit that represents only a few thousand years.

5.5.4 Conclusions

Overall the BACT analysis demonstrated more differences in blank production

than toolkit morphology. This finding was surprising given that previous studies of

technological change at Nasera, and at Mumba, highlighted changes in tools as major

shifts (Diez-Martín, et al., 2009; Mehlman, 1989). It is possible that the sample sizes for

several analyses were too small to adequately reflect the central tendency of each level.

In the broader view of cultural transmission of stone tool manufacture, and in light of the

results of Chapter 2, it is possible that the changes in blank production are reflective of

information transfer.

The most pronounced shift in blank production occurred between Units IV and

III, which is surprising because both of these geological units correspond to what

Mehlman defined as the Kisele industry. The shift in blank production is likely driven by an increase in bipolar flaking in Unit III (Levels 12-17) relative to Unit IV (Level 18-25).

These results, in conjunction with Mehlman’s data, indicates a shift in core reduction

137 strategy within the MSA, before the MSA-LSA transition. A similar pattern was also

observed in Bed V at Mumba with a shift toward bipolar (Eren, et al., 2013). Tryon and

Faith (2016) demonstrated that shifts toward decreased residential mobility occurred after the Nasera industry, and that occupation span index (OSI) (Surovell, 2012) and artifact density were relatively low for both the Kisele and Mumba industries. Thus it is unlikely that the core reduction shift within the MSA at Nasera is a result of demographic change.

One potential explanatory model relies on raw material use. Whether or not the shift in core reduction strategy is a cause or an effect of the raw material shift remains to be seen. However it should remain a cautionary tale: before invoking complex causal mechanisms for shifts in technology, like direct cultural transmission between groups, simpler mechanisms should be ruled out. The shift in raw material could reflect a higher reliance on locally available material which itself could reflect changing demographic structure (Eren, et al., 2013), but such conclusions merit additional research, particularly regarding raw material availability and use at Nasera.

One major caveat of concern when applying BACT to MSA assemblages regards taphonomy. These analyses suffered from multiple levels of information loss. The first stage of information loss occurred at deposition, virtually nothing is known about the site formation processes at Nasera. The presence of RMUs and lithics < 2 cm suggests little post-deposition winnowing, but the broader site formation processes that produced the site (e.g. sediment accumulation rates) remain to be seen. The next stage of information loss occurred at excavation, as the assemblage was actively destroyed (Flannery, 1982:

275). Mehlman’s detailed excavation and recordkeeping mitigated this issue, but the very process of curating the assemblage altered the visibility of patterns. For example, the

138 assemblage analyzed in this study consisted mostly of angular waste, rubble, and rolled pieces, pieces that undoubtedly received less attention in previous analyses than retouched tools. Another loss of information occurred after Mehlman’s curation efforts, as researchers re-arranged the assemblage, exported parts of it, and parts of it simply disintegrated. Finally, loss of information occurred with the present analyses, due to time constraints, methods constraints (e.g. inability to capture 3D morphology), and the author’s own biases (e.g. emphasis on core reduction strategy).

The current study attempted to apply a BACT approach to the MSA-LSA sequence at Nasera rock shelter. This approach elucidated some technological differences not discussed by Mehlman, particularly in blank production between Levels 18-25 (Unit

IV) and Levels 12-17 (Unit III). The least difference occurred between Units I and II

(Levels 8/9-10 and Levels 6+7). This result is surprising given that Tryon and Faith’s

(2016) results indicate that a trend toward decreased mobility initiated with the Nasera

industry. Thus it remains to be seen if changes in demographic structure, such as

increased population density, influenced technological patterns at Nasera. A most likely

explanation is that taphonomic processes, both post-depositional and post-excavation, have obscured such patterns. The unique and informative sequence at Nasera thus deserves further analysis before conclusions regarding cultural transmission at the site can be confirmed.

139 Chapter 6. Late Pleistocene Cultural Transmission at East Turkana: Taphonomic and Site Formation Perspectives

6.1.1 East Turkana History of Research

Despite well-documented Plio-Pleistocene and Holocene records, the Late

Pleistocene record at Koobi Fora remains largely enigmatic. In 1991 and 1992 Alison

Kelly undertook the first formal examination of Late Pleistocene East Turkana under the guidance of J.W.K. Harris in conjunction with the Koobi Fora Field School. Kelly’s research focused on three main exposures: the Koobi Fora ridge, the Karari escarpment, and erosional scarps near Ileret town. Kelly excavated five sites reviewed below. The results of this research are published in Kelly (1996) and Kelly and Harris (1992).

Ileret Region

FwJi1

FwJi1 (Area 6A) yielded a hominin femur (KNM-ER 999) in 1971. This femur exhibits morphology consistent with Levantine Skhul-Qafzeh hominins (Trinkaus 1993).

In 1974 Professor J.W.K. Harris excavated the site to determine the stratigraphic relationship of the hominin femur. The stratigraphic position remains unclear and is likely located in the upper Chari Member, 8 meters above the Chari tuff, according to unpublished notes from Frank Brown. Harris’ survey and excavation yielded weathered scatters of surface artifacts and fossils that appeared to be MSA, and thus Kelly returned to this site first in her 1991 survey. Kelly carried out a 5 x 2 m step trench, followed by a

2 m extension on the northern end of the trench.

The excavation was conducted in 10 cm spits. Kelly describes two archaeological horizons, A and B, which were separated by a calcareous sandstone unit. The stratigraphic descriptions by Kelly and Harris are largely in agreement. The Kelly

140 excavation yielded 33 total in situ and surface artifacts. Kelly recorded the highest density of in situ artifacts in Horizon A, a reddish brown moderately sorted sand with calcium carbonate nodules. 57% (n=19) of the assemblage is silicaeous and 33% (n=11) is basalt. Kelly’s excavation also yielded 19 identifiable fish bones. One cut-marked bone was found in 1990, a left os coxa acetabular fragment of Damaliscus sp.

A hominin cranium (KNM-ER 3884) was also found nearby in Area 5 that exhibits modern Homo sapiens morphology (Brauer, et al., 1992). According to Kelly, the fragments appear to derive from undifferentiated sediments below the Galana Boi formation. She recovered no archaeological or paleontological material upon revisiting the site and thus no excavation was conducted.

FwJi2

Kelly reported an excavation in Area 17 at FwJi2, which she discovered in 1990 while surveying east of the Ileret airstrip. FwJi1 consists of a kilometer-long outcrop running north-south. In 1990 Kelly conducted two 5x5 m surface collections, yielding

102 lithics. A subsequent 1x3 m geological trench of 80 cm depth yielded 5 in situ artifacts. Kelly abandoned the excavation due to low density of artifacts and fauna. The majority of lithics (86%) recovered from FwJi2 are cryptocrystalline silica (CCS) such as chalcedonies, fossil wood, and cherts. Kelly also reports several cores with radial preparation (Kelly 1996, Plate 3.2). 206 bone and bone fragments were recovered from the site, 101 of which are turtle carapace fragments.

FwJi3

The final site actually excavated by Kelly in the Ileret region is FwJi3, discovered by Kelly in 1992 while surveying near FwJi2. According to Kelly, FwJi3 initially

141 appeared to consist of MSA surface artifacts locally derived from a small capping deposit atop a small ridge, though she gave no explanation as to why they should be considered

MSA. Kelly laid two 5x1 m grids for surface collection. She then excavated beginning in the N4-5/E0-1 square of this grid and determined that the artifacts were located in a discrete horizon 0-20 cm depth at the top of the ridge. The other squares in her grid system were downslope from this horizon. Therefore only the one 1x1 m square capping the ridge contained in situ artifacts; all other artifacts from FwJi3 are presumed to have eroded from this horizon and were surface collected downslope.

296 artifacts were recovered from FwJi3, 64 of which were in situ. Kelly reports

14 core fragments and 11 prepared cores from the site. 83% of the combined surface and in situ assemblage is CCS. 215 bone and bone fragments were recovered, including

Hippopotamus amphibius, Megalotragus sp., and one small primate.

Karari Region

FxJj66

The FxJj66 locality is located in the Karari region and was discovered by Kelly in

Area 112 in 1990, consisting of deflated surface MSA artifacts on a gently sloping hill

500m in length. Due to the deflated nature of the deposit she did not conduct an excavation. Instead she conducted a 5x5m surface collection of 177 lithic artifacts. No faunal remains were located in the surface grids, lending further support that the site was deflated and exposed to the sun for a long period. The deflated surface collection consisted of 132 CCS artifacts and 39 basalt artifacts.

142 FxJj61

FxJj61 was discovered by Kelly in Area 112 in 1991, consisting of, “a sinuous erosional outcrop down-cut by erosional streams” (Kelly 1996:139). Kelly first mapped the entire outcrop and placed six random1x2m trenches along the outcrop. In 1992 she continued excavating the northern end of this outcrop, excavating 15 square meters of deposit to 90cm depth.

Stratigraphy of the six trenches suggested 5 layers. No artifacts were found in these trenches. In the excavations, Kelly recovered 90 in situ artifacts and 315 surface collected artifacts including radially prepared cores and “retouched flakes, side scrapers, points, notched pieces, and picks” (Kelly 1996:156). Kelly observed a lower frequency of

CCS at FxJj61 relative to both the Ileret localities and FxJj66. She also noted that basalt frequency was higher in the surface assemblage and lower in the excavation in than any other locality. Size class distribution indicates a lack of small (< 10 mm) artifacts, indicating post-depositional winnowing (Shickc 1987). However three conjoining artifacts were found, as well as three conjoining horn core fragments. It is unclear if the conjoining artifacts were broken on site or are technological re-fits. 56 bone and bone fragments were reported, half of which are unidentifiable. The identifiable fragments are mostly mammalian, in addition to Hippopotamus amphibius. Attempts by the author and

J.W.K. Harris to relocate this site in 2015 and 2016 were unsuccessful.

143 Koobi Fora

GaJj17 – Kelly Excavation

In Area 4 near Koobi Fora Charles Nelson located this MSA deposit atop a steep

hill (N 3.96°, E 36.30°). Kelly re-located and excavated GaJj17 in 1991. She conducted a

1x2 m geological trench, three 5x5 m surface collections, and three 1x1 m squares

excavated to 20 cm depth using 2 cm sieves. Kelly concluded that the artifacts derived

from indurated sandstone capping the site, and that the deposit was sterile starting at

20cm depth.

Kelly recovered 463 lithic artifacts from GaJj17, including both surface and in

situ pieces. She noted several conjoining artifacts, and a lack of small (< 10mm) artifacts.

She also noted that for the in situ assemblage, basalt frequency was highest and CCS frequency was low relative to all other localities.

GaJj17 – Re-excavation

In 2015 the author re-located GaJj17 and in 2016 re-excavated the locality with one 2x1m excavation and one 5x1 step trench. In 2017 this excavation was expanded by

2 m to the north, reaching a maximum depth of 1.8 m. Stratigraphy of the excavation was described as two major units: an upper deposit consisting of loose light gray sand and sandstone of variable size, and the lower one consisting of lenses of interbedded dark and orange sands with rare sandstone. The upper deposit is approximately 70 cm thick. It revealed archaeological finds, including 10 artifacts and 30 mammal and fish bones that, unlike those from Kelly’s excavations, have been piece-plotted. With sieve finds

included, there are 35 lithic artifacts and 830 bone fragments overall. Finds were

144 discovered both in the sands and incorporated into the consolidated sandstone. Lithic

artifacts were predominantly basalt and ignimbrite, and included mainly detached pieces,

including Levallois flakes, as well as blade and flake fragments. No cores were recorded.

Orientation data suggest a SE-NW alignment of elongated objects indicating post-

depositional movement.

Before geo-trench 1 was excavated, surface finds were collected from the

surrounding area, yielding 85 artifacts and fossils. Geo-trench 1 was excavated in 4 steps,

each of which is 60-70 cm height. Artifacts and bones were recovered, though not in high

density, and thus were not systematically plotted. A higher artifact density was found at

the bottom of the fourth step. At this level, a 1x1m square aligned to the arbitrary

excavation grid was opened to reveal this higher artifact concentration. Given that part of

this square has been dug during the geo-trench excavation, only its southeast corner was

excavated and 10 artifacts and fossils were plotted.

Systematic surface collection was done in 6 m2 (N79-82E79-81) yielding 76

artifacts and bones. These surface lithics were predominantly CCS and basalt. Levallois

blanks, ostrich eggshells, fish and mammal bone were recovered from the surface,

including one bone harpoon. Surface finds were collected before geotrench 2 was

excavated. Geotrench 2 did not produce any archaeological or faunal finds.

East Turkana Summary

Kelly concluded that raw material procurement was the most significant variable

driving technological variability in the eastern African MSA. She also argued that the low artifact density that characterizes the Koobi Fora MSA sites is unique relative to other

145 Kenyan MSA sites. Kelly argues that the region was likely arid in the early Late

Pleistocene, and thus would not have been a hospitable region for hominins.

Alternatively, Kelly proposes that differential site formation processes unique to Koobi

Fora may have caused the low artifact density.

Dating attempts for the later Pleistocene of Turkana have been largely unsuccessful. This is due to an incomplete understanding of the geomorphology of this time period. The Koobi Fora Formation is capped by a major unconformity. The uppermost dated tuff in the Koobi Fora Formation is the Silbo Tuff, dated to 750 ka.

Dates that stratigraphically lie above the Silbo Tuff, like the Kale tuff and Unnamed Tuff, await age estimates. The stratigraphy of the uppermost Koobi Fora Formation is therefore poorly understood, particularly above the Silbo Tuff within the Chari Member. The

Guomde Beds were defined by Bowen (Bowen, 1974) as consisting of sediments above the Chari Member of the Koobi Fora Formation and below the Galana Boi Formation, dated to the Holocene (Bloszies, et al., 2015). However, due to lateral inconsistencies and a general perception that these sediments were not lithologically dissimilar from the KF

Fm., the Guomde Beds were eventually subsumed into the KF Fm. (Brown and Feibel,

1986).

Recent fieldwork, however, has provided positive results that sediments overlying the Silbo Tuff and underlying the Galana Boi Formation can be stratigraphically correlated across space (Mavuso et al, In Prep). Figure 6-1 shows the correlation of these sediments, tentatively referred to as SSM, within the Ileret region. It is possible that SSM is a recent manifestation of what Bowen described as the “Guomde Beds”. These sediments correspond to Kelly’s FwJi1 locality.

146

BACT analyses (Tostevin 2012) were done across space at East Turkana to ask

the question: were MSA technologies different across different environments? Analyses

were binned according to spatially defined locations following paleontological collecting

areas. These three units of analysis were: Karari Ridge, Koobi Fora, and Ileret. By

applying BACT to spatially defined units of analysis, broader scale trends in technology

can be elucidated.

Figure 6-2 shows the study localities. Ileret is considered a near-shore environment, whereas the Karari ridge is considered a non-lakeshore environment. Data were also analyzed from GaJj17, which is located in the Koobi Fora region. GaJj17 micromorphology results, combined with Holocene high lakestand models, suggest that at the time of artifact deposition, GaJj17 was nearer to the lakeshore. Therefore it is

147 expected that Ileret and GaJj17, both near-shore localities, will exhibit more similarities

to each other, and that the Karari localities will be distinct from both of these.

Figure 6-2. Study localities at East Turkana.

6.3 Composition of the East Turkana Dataset

The data analyzed here comprise multiple datasets collected from 2013-2016. In

2013 materials from Alison Kelly’s excavations were studied (n=114). These included

FwJi2, FwJi3, GaJj17, and FxJj61. In 2015 artifacts collected during MSA survey with the KFFS were collected and added to this database (n=110). Further data were collected and measured from survey and excavation of GaJj17 during the 2016 season at KFFS

(n=80). These combined data (n=304) include 56 cores, 140 complete flakes, and represent a diversity of raw material (Kelly and Harris, 1992; Kelly, 1996). Alison

148 Kelly’s trays are organized with mixed artifacts and faunal remains. Only artifacts with

provenience information were chosen for study, with emphasis on artifacts of in situ

context. For example, FwJi2 is almost entirely surface collected and therefore study of

this assemblage is mostly qualitative.

Given the likely deflation that occurred during Late Pleistocene high lake stands

(Bloszies, et al., 2015; Butzer, et al., 1972), it is impossible to know the date of these

artifacts, or the degree to which they are time averaged. Landscape geomorphology

research is underway, incorporating sedimentary facies analysis, tephrostratigraphy, and

optically stimulated thermoluminescence (OSL) dating (Ranhorn, et al., 2017; Warren, et al., 2017; Ziegler, et al., 2017). Until these efforts yield conclusive results, however, the chronological context of the Koobi Fora materials remains speculative.

Table 6-1. Koobi Fora Measured Lithic Dataset.

Blade or Complete Flake Locality Blade Core Total Flake Fragment Fragment FwJi2 2 11 14 28

FwJi3 1 11 20 1 37 FxJj61 14 13 7 36

GaJj17 54 3 35 93

Ileret Surface 23 5 6 34

Karari Surface 7 27 1 40 76 Grand Total 10 140 56 89 304

149

Figure 6-3. Koobi Fora Raw Material Diversity.

Figure 6-4 compares reduction intensity distribution of complete flakes across the East

Turkana landscape. Using normalized scar count as a proxy for reduction intensity, lower

NSC represents earlier stage reduction and larger NSC represents later stage reduction.

The dataset was binned into Near Lake and Escarpment. Near Lake assemblages include

Ileret localities and GaJj17. GaJj17 is further from the modern lake than the Ileret localities, however GaJj17 is in line with the Ileret localities, particularly those in Area 7, with respect to longitude. Thus it can be reasonably posited that both areas had similar access to lacustrine resources. Escarpment assemblages in this analysis derive from

Karari localities, including FxJj61.

Both the Near Lake and Escarpment assemblages show a normal distribution of NSC

(Shapiro Wilk Escarpment W=0.922, p=0.24; Near Lake W=0.96, p=0.39). However, the

150 Near Lake group shows higher tail to the right, indicating a higher abundance of later

stage reduction flakes.

Figure 6-4. Koobi Fora Reduction Intensity. In general two “technological packages” are present at Koobi Fora. The first pattern is basalt-dominated and consists mainly of large, radially prepared, often convergent flakes. The most obvious occurrence of this lies at FxJj108. Retouched tools in this suite are rare. The second technological pattern at Koobi Fora is CCS-dominated, composed of elongate thin flakes that are often retouched with edge damage, including denticulates, scrapers, and points. These two technological suites may likely be driven by access to raw material sources and/or fracture mechanic differences between chert and volcanics (Tryon, et al., 2008). The most obvious occurrence of this is in Area 7 from a deflated surface deposit. The temporal relationship of these two technological patterns is currently unknown. One possibility is that the basalt-dominated technology is older, possibly late Acheulean, whereas the CCS-dominated assemblages date to the later MSA.

151 Alternatively the two technologies overlapped in time. GaJj17, which remains undated,

exhibits both patterns.

6.3.1 East Turkana BACT Results

Platform Thickness

Table 6-2. Platform thickness descriptive statistics.

Koobi Fora Karari Ileret mean 5.55 4.67 6.43 sd 3.43 5.00 2.52 n 40 26 31

A Kruskal Wallis test showed a significant difference in platform thickness between the sample medians (p = 0.003, H = 11.44). Pair-wise Mann Whitney U test

showed that this difference likely is attributable to Karari and Ileret being significantly

different (p < 0.01, U = 186).

Table 6-3. Pair-wise Mann Whitney of platform thickness.

Koobi Fora Karari Ileret

Koobi Fora - 0.07 0.09 Karari 0.07 - < 0.01 Ileret 0.09 < 0.01 -

External Platform Angle

Table 6-4. EPA descriptive statistics.

Koobi Fora Karari Ileret mean 80.71 74.05 80.15 sd 8.75 8.59 11.61 n 34 19 13

152

Similar to platform thickness, a Kruskal Wallis test showed a significant

difference among the three sample medians for external platform angle (p = 0.03, H =

6.82). However unlike platform thickness, a pair-wise Mann Whitney U test showed that the difference in external platform thickness is attributable to differences between Karari and Koobi Fora (Table 6-5).

Table 6-5. EPA pair-wise Mann Whitney results.

Koobi Fora Karari Ileret Koobi Fora - 0.01 0.62 Karari 0.01 - 0.16 Ileret 0.62 0.16 -

Dorsal Surface Convexity

Length/Width Ratio

Table 6-6. Length/Width ratio at East Turkana.

Koobi ForaFor a Karari Ileret mean 1.35 1.78 1.37 sd 0.72 0.87 0.25 n 31 28 35

Table 6-7. Mann-Whitney pair-wise tests for length/width ratio at East Turkana.

Koobi Fora Karari Ileret Koobi Fora - 0.01 0.16 Karari 0.01 - 0.04 Ileret 0.16 0.04 -

In terms of core exploitation, sample size was too low at GaJj17 to compare

(Figure 6-5). However there appear to be opposite patterns between Ileret and Karari.

153 Ileret is dominated with peripheral flaking strategies whereas Karari is dominated by bi-

or uni-directional flaking.

100% 90% 80% 70% 60% 50% Peripheral 40% BiOrUni 30% 20% 10% 0% Ileret Karari

Figure 6-5. Core orientation at East Turkana.

6.3.2 Discussion and Conclusions

This study presented results from ongoing research at East Turkana regarding the

MSA, and applied a BACT analysis to determine to what extent technologies changed in

different environments. Ongoing fieldwork in geomorphology and sedimentology

confirms prior sedimentological work by Vondra and Bowen (1978), demonstrating the

presence of lithologically distinct sediments in the Ileret region that lie stratigraphically

above the known Chari member and stratigraphically below the Galana Boi Formation.

These sediments, tentatively described as SSM, are associated with in situ MSA deposits,

including FwJi1 (Mavuso et al, In Prep). Research is ongoing to date these sediments,

both using argon-argon methods to date in situ tephra above the Silbo tuff, and OSL dating of sand deposits at FwJi1.

154 Additional ongoing excavations at GaJj17 in the Koobi Fora region confirmed the

in situ nature of MSA deposits in this region. Excavations from the 2016 and 2017 field

seasons resulted in over 5.6 m2 of excavated sediment in which two Levallois points were

uncovered approximately 1 m below the surface. Additional flakes and blade fragments

were uncovered in situ of chert and ignimbrite in addition to fossil fauna, predominantly

fish and hippo. Structural geological analyses suggest that the site formed near faults in

the Koobi Fora region, such that the site was uplifted and therefore protected from later

Holocene high lakestands which demolished the later Pleistocene record elsewhere in the

region. Micromorphological and sedimentological analyses of the stratigraphic sections

suggests that the site was fluvially deposited in its early stages, and later mixed with

aeolian deposition in its recent stages (Ziegler, et al., 2017). Fabric analyses and size

sorting of fossils and artifacts suggest that some post-depositional winnowing took place

(Ssebuyungo, et al., 2017). Ongoing OSL research by Dr. Debra Colarossi at the Max

Planck Institute in Leipzig should reveal the sequence age estimates.

BACT analyses of the East Turkana assemblages suggest stark differences between the Koobi Fora and Karari, and Ileret and Karari, but consistent similarities between Koobi Fora and Ileret. Within a single domain, platform maintenance, different steps present different trends: platform thickness showed the largest difference between

Ileret and the Karari, whereas differences in EPA are most robust between the Karari and

Koobi Fora. Elongation index suggests that Karari data are different from both Koobi

Fora and Ileret. This is further evidenced by the stark difference in core types between

Ileret and Karari, with Karari showing an abundance of uni- and bi-directional cores which may represent a tendency toward blade production. In all three comparisons Koobi

155 Fora and Ileret attributes are consistently similar. This supports the hypothesis that near-

shore localities may have exhibited functional requirements that required similar

technologies. Reduction intensity analysis suggests that assemblages near the lake are

more reduced than those on the Karari ridge. This may be related to distance to raw

material (Tryon et al 2008) but raw material availability, particularly of chert resources,

for Turkana is currently unknown.

In conclusion, the East Turkana region represents a promising area for further

MSA study. Current in situ evidence suggests that MSA foragers structured their

technology across the landscape, such that near-shore localities were more similar to each

other than localities on the Koobi Fora ridge. It is impossible to confirm at this stage if

these differences represent different functional needs or different cultural transmission

chains, or both. These analyses were constrained by a limited sample size and poor

chronological control. Further geomorphological and dating work is needed to improve

the chronological context of the deposits. With a higher resolution Late Pleistocene

record for East Turkana, it will be possible to develop a paleo-lake model similar to that of the Holocene (Bloszies, et al., 2015). Such a model, coupled with a better understanding of the faunal distribution across the paleolandscape, will enable various hypotheses regarding the role of cultural transmission and the emergence of human pro- sociality to be formally tested.

156 Chapter 7. Conclusions

This research was undertaken in order to determine the extent to which Late

Pleistocene regional patterns in eastern African tool technology reflect the high fidelity transmission of cultural information, or other non-behavioral constraints. This question, attempting to explain patterns in technology in terms of social or environmental contexts, is one of the most central aims in Paleolithic archaeology broadly. The goal of this dissertation was to provide a fresh look at the evidence with cutting edge methods. As such, method development and refinement was a central component of this work. The results of this work that are most likely to impact the broader field of archaeology are the novel methods, particularly regarding cultural transmission, that were created and applied in this dissertation.

At the outset, a dissertation asks a “large research question” and breaks up the research into a list of hypotheses. This dissertation used a series of contingent hypotheses in which the later steps were contingent on previous ones to elucidate the role of cultural transmission in stone tool assemblages. Simply put, this work can be conceptualized with the following scheme: What do we measure? How do we measure? And finally, when applied to the archaeological record, what are the patterns in our measurements?

The first third of this project, comprised of social learning flint knapping experiments, asked the question, “What aspects of lithic assemblages do we measure if we are interested in questions of cultural transmission, learning, and ultimately— demography?” This question was a prerequisite to studying the archaeological record, because a lithic analyst has at their disposal any number and combination of attributes that can be measured, and at the outset of this dissertation, none of those attributes were considered “better signatures” of social transmission than any others.

157 Middle range studies are perfectly suited for this problem, because thy enable

archaeologists to study a range of behavioral phenomena in controlled systems, to vary

stimuli, and to measure responses to those stimuli. Within the field of lithic analysis,

middle range research largely comprises flintknapping experiments, such as reproduction

of ancient technologies (Pelegrin and O’Farrell) or precise characterization of knapping mechanics (Dibble and Rezek). How these studies are used to interpret behavior in the

Paleolithic varies across researchers and are conducted by researchers in both the chaîne opératoire and reduction sequence schools of thought. The hypothesis developed in this component of the dissertation stated, “Differential degrees of information transfer are detectable in measurable signatures in lithic assemblages.” The social learning experiments conducted to answer this question represent the single largest component of the dissertation, because it represented the most obvious “gap” in knowledge between the fields of Paleolithic archaeology and social learning. For example, creating the standardized porcelain cores needed to effectively control nodule shape and size was a considerable undertaking. Finding knappers who are efficient at controlled flaking but blind to the Levallois method proposed another challenge. Nonetheless, the experiments were successful and provided key results.

The most central take-home message from these data suggest that social learning in stone tool production takes place both at the level of individual strikes/blows and also at the aggregate level of core reduction strategy, but the attributes associated with the former are so susceptible to equifinality that gleaning any pattern of learning from them is spurious. The variables most useful in predicting degree of information transfer were

158 number of direction changes on a core or flake, and technological flake category when

binned by reduction stage.

These experiments point to the need of lithic analysts interested in cultural

transmission to study reduction sequences or chaîne opératoire, not end form alone.

These results stand in stark contrast to a large current literature which studies cultural

transmission in lithic assemblages by ignoring reduction sequences and focusing solely

on geometric morphometrics of end form. In sum, this component of the dissertation,

following the pioneering research of Tostevin (2012), represents an advance in the

knowledge of how cultural transmission is embedded in stone tool production sequences.

The second phase of this dissertation asked the question, “Given a series of

attributes determined in phase one of this dissertation, and in other studies, to be relevant

to cultural transmission and social learning, how do we measure them?” This question

stemmed from the premise that repeatable methods are a requisite basis of all research.

Given the findings of the previous chapter which suggest that technological process, not

stone tool form, are the key to gleaning patterns of social learning from lithic

assemblages, this second component of the dissertation sought methods to study

technological process quantitatively in a way that is repeatable by multiple analysts. At

the outset of this dissertation, Paleolithic archaeology lacked a consensus of how to

recognize key core reduction strategies in the archaeological record, particularly

Levallois (Perpère, 1986). Levallois was therefore used as a case study due to its pervasiveness in Middle Stone Age and Middle Palaeolithic assemblages and its potential implications for social learning (Lycett, et al., 2016).

159 In the research outlined here, expert knappers flaked nodules according to

technological rules as outlined in Boëda (1995), creating the experimental Levallois and experimental discoid datasets. The author then converted Boëda’s technological rules, known as the volumetric conception, into basic geometric variables that can be captured

in three-dimensional space. The research here took advantage of burgeoning 3D imaging

techniques, particularly photogrammetry, to scan the cores and measure the variations of

the technological attributes. Four main variables were studied: upper:lower volume ratio,

upper:lower angle ratio, primary flaking angle, and upper angle average. This approach

capturedthe relative hierarchy of flaking surfaces and can be repeated by multiple analysts to elucidate ranges of variation. Thus the project did not attempt to assign lithic

artifacts to categories (i.e. “Levallois or not”), but ratherto convert Boëda’s technological

guidelines, which define the Levallois method, into variables that can be visualized as

ranges.

When applied to archaeological specimens the 3D approach found that few

specimens met all of Boëda’s criteria for Levallois. For example, cores may exhibit

relative flaking hierarchy but not a flaking plane that is sub-parallel to the flaking surface.

This approach highlights the need to independently study technological variables which

can then be aggregated to elucidate the pattern of core reduction. The 3D methods created

here to quantify variation in Levallois reduction can be used across time and space to

enhance comparative studies.

While the 3D Levallois study provided analytical methods for capturing

technological variation in core reduction, a clear caveat with the study remained—how

are the technological variables affected by stage of reduction? As detailed in Chapter 3,

160 stone tool manufacture is a reductive process in which technological decisions can be constrained as geometry changes with each flake removal (Odell and Henry, 1989).

Given that a central aim in this dissertation is to study cultural transmission in lithic assemblages, and given the results of the previous phase which suggests that cultural transmission patterns should be gleaned by studying core reduction strategies as a whole, a necessary next step in answering, “How do we measure?” is to determine to what extent technological variables related to core reduction strategy vary across the reduction sequence. Reduction intensity of stone artifacts (e.g. early stage, middle stage, or late stage) can be conceptually compared to allometry, how shape changes with size, in morphological studies. Comparing entire assemblages with other assemblages without prior binning according to reduction stage may obscure patterns of core reduction strategy. At the outset of this research, the most common way to control for reduction stage involved using variables like cortex amount and location (e.g. Toth’s technological flake category). However the utility of Toth type and other variables to elucidate reduction sequence were based largely on Oldowan reduction methods (Braun, et al.,

2008).

To confirm the utility of these variables to elucidate reduction stage in prepared core assemblages, this research again turned to middle range experimental studies.

Following the methods of Braun et al 2008, one expert knappedr conducted 20 experimental reduction sessions, 10 of which utilized the prepared core Levallois method as outlined by Boëda, and 10 of which utilized bifacial flaking usedtypical of handaxe production. Using bifacial reduction as a comparison for the prepared core assemblage

161 created an additional experimental referential dataset, when combined with the results from Braun et al 2008, which focused on Oldowan reduction methods.

As detailed in Appendix A, the variables used to predict reduction stage in

Oldowan assemblages and Acheulean assemblages do not all accurately predict reduction stage for prepared core assemblages. This result is likely due to the differential geometric approach used in the Levallois method, in which one surface is preferentially reduced relative to others, causing a differential loss of volume. The one variable that best predicts reduction stage in the Levallois sequences was normalized scar count (number of dorsal scars divided by the log of the flake area) (Braun 2008). This variable reflects the number of flake scars relative to the size of the artifact, because size overall decreases as cobble size reduces. Surprisingly, technological flake category was not a strong predictor of reduction stage for the Levallois dataset , likely because cortex can be present on later stage artifacts as the preparation (lower) surface is shaped; it is not uncommon for archaeological Levallois cores to exhibit cortex on this surface after discard.

The social learning flint knapping experiments, 3D Levallois study, and reduction stage experiments all comprised the first two-thirds of this dissertation, asking the questions, “What do we measure?” and, “How do we measure?” The last component of this dissertation focused on quantifying patterns of these attributes in the MSA of eastern

Africa. As detailed in Appendix A, six assemblages were studied: Muguruk, Prospect

Farm, Kisese II, Nasera, and Koobi Fora. Artifacts were selected based on chronological age, although in many cases this was unknown.

The first major conclusion of the Paleolithic assemblage characterization study is the dire need of cultural heritage management intervention by foreign scholars. Glynn

162 Isaac was one of the most vocal scholars about this issue and since his passing, few have

taken over. The situation in Tanzania is such that many foreign researchers opt simply to

privately store excavated collections in order to guarantee longevity of the curated

material. The impact that this approach, positive or negative, will have on future scholars

remains to be seen. The research presented here clearly suffered from a lack of

assemblage management.

Once a general understanding of each assemblage was obtained, in terms of raw material, integrity, age, and reduction intensity, the final phase of research applied the results of the cultural transmission experiment and other studies to specific components of the archaeological data obtained in Appendix A, in order to maximize ‘like with like’

comparisons, and to test specific models of cultural transmission. This final phase built

largely on Tostevin (2012) and employed his lithic analysis methods—a ‘behavioral

approach to cultural transmission’ (BACT).

The first analysis used the Nasera sequence to test models of cultural transmission across the MSA/LSA transition. As detailed in Chapter 5, the results suggest that a large

‘gap’ in continuity, or shift in technology, occurred between Levels 12-17 and 8/9-11.

This time period coincides with what Mehlman referred to as a shift from the Kisele and

Mumba industries and was driven largely by the shift from centripetal/periphal flaking

strategies to platform and bipolar flaking strategies. Despite this apparent “shift” in

technology, it is important to note that other differences occurred in different domains at

various time intervals, particularly between Levels 18-25 and Levels 12-17. This latter

shift is important because it occurred within the MSA. Overall the results indicate that a

re-analysis of the Mumba and Nasera industries is merited, as these phases are likely

163 much older than currently thought. As such, the cultural transmission model that best fits

the MSA/LSA transition likely reflects the punctuated model (Tryon, et al., 2015b). The response to technological variables to changing demographic structure, particularly during the upper part of the sequence, requires further analysis.

The Koobi Fora BACT analysis, unlike the Nasera analysis, compared technological patterning across space according to different places on the landscape (Koobi Fora, Ileret, and Karari). These results suggest that technological similarity was greatedst between

Ileret and Koobi Fora, whereas Karari appears to be an outlier in MSA technology. The

Karari data suggest an increased representation of blade production as seen with the

increase in platform cores and increased elongation index. While more work is needed to

confirm this pattern, one potential explanation is that both Ileret and Koobi Fora localities

were near-shore sites, and thus the similarities there may reflect functional needs. The

distance between the Koobi Fora locality (GaJj17) and the Karari sites (< 20km) is well

within the known foraging radius for modern foragers. In terms of answering the original

research question, whether technological patterns across space reflect increasing

adaptation to specialized environments or cultural transmission, the East Turkana

paleolandscape likely represents both a functional and environmental signal (e.g. fishing

near the shore, hunting near Karari). However given the small dataset and lack of

chronological resolution in the study, more work is needed to confirm or deny this

possibility.

Several caveats characterized this work. The clearest and biggest problem with

this dissertation is that the methods developed in the earlier stages of the research were

not easily applicable to the archaeological dataset studied later. The majority of cores

164 studied were less than 3 cm and could not be modeled in 3D, precluding the technological analyses outlined in Chapter 3. Also, the variables determined to be associated with cultural transmission in Chapter 2 are often unreadable on quartz, especially flake scar directionality and cortex. This was also the case for variables determined to be strong predictors of reduction sequence (normalized scar count), because clearly demarcated flake scars are not easily observable on quartz.

There are several ways that the conclusions of this dissertation can and should be

expanded upon in future studies. The most obvious need is to increase chronological

resolution at both Nasera and at East Turkana, and ideally at all of the study localities.

Future work should increase sample sizes, because once assemblages are binned, for

example by reduction stage and then Toth type, sizes are often less than 10-20 specimens.

More specimens from Koobi Fora localities, particularly cores, are needed to aid in

comparative analysis.

Research is ongoing to mitigate the issues encountered regarding raw material and

flaking mechanics. First, the standardized porcelain nodules used in the experiments in

this dissertation are being refined to improve the shape in order to ease opening of the

nodule, and variations of the heating protocol are underway to produce a more flint-like knapping material. Additionally, improvements have been made in 3D modeling of quartz with photogrammetry. Quartz cores from GvJm16, for example, were successfully modeled using talc powder and a photogrammetry rig (Porter, et al., 2016). While quartz is by no mean unique to Africa, it is absent from many of the localities where advances in lithic analysis take place and tend to be flint-rich (e.g. western Europe, central Europe, the Levant). As such, developing quartz-specific methods, such as middle-range tested

165 proxies for core exploitation, will be important in order to adequately capture the

complexity of quartz artifacts worldwide. Without quartz-specific methods, lithic analysts

run the risk of attributing quartz assemblages as “crude”. This is the case both in

contrasting African lithic traditions with the rest of the world (e.g. Callahan, 1987), and in North America, where quartz flaking traditions have been common but largely unstudied (Jones, 2006).

When viewed broadly, patterns of reduction were observed within raw material categories, especially quartz. At multiple sites, quartz pebbles were split with bipolar technique and then worked centripetally. This approach is also seen at Congolese

MSA/LSA sites (Cornelissen, 2016). Additionally, technology appears to track raw material use (e.g. at Nasera and Mumba). Many of the defining characteristics of the

MSA/LSA transition—lack of Levallois, increase in platform and bipolar strategies, appearance of backed blades, disappearance of points—may be attributable to the shift to crystalline tool stone from cryptocrystalline materials. Thus, one important question for future research regarding Late Pleistocene foragers is: what caused a shift in raw material use? To answer this question will require additional data spanning the MSA/LSA transition at open-air sites, in order to holistically capture forager landscape use at this time interval.

In conclusions, this dissertation led to more questions than answers. It developed new methods in lithic analysis, particularly in understanding the role of social learning and cultural transmission on stone tool variability. It created and applied novel 3D approaches to study technological process, and determine which variables can, and cannot, accurately predict reduction stage. The final phase of this dissertation is the least

166 developed in its current state, and arguably represents a career’s worth of research questions. The models of cultural transmission related to a) the MSA/LSA transition in

Tanzania and b) the mobility and land use of foragers at Koobi Fora, both will require long-term research projects.

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192 Appendix A. Levallois Reduction Models

A.1. Introduction

A.1.1. The Problem: Why Reduction Stage Matters

Stone tools are produced along a continuum of volume reduction as flakes are continually removed from a nodule. This continuous volume reduction results in a nodule that is both smaller and geometrically altered with each flake removal, thereby changing the number and placement of sufficient platforms for further flake removals and constraining knapper behavior (Odell and Henry, 1989).

As such, variables associated with flintknapping behavior (e.g. platform thickness, external platform angle, direction of flake removals) are expected to change along the reduction sequence. Previous studies have documented these relationships using linear regressions. For example, in cobble reduction experiments in which flakes were labeled as they were removed, flakes removed later in the sequence were associated with decreases in flake length, flake width, and cortex (Braun, et al., 2008). The strength of correlations differed across variables (ibid).

Figure A-1. Idealized reduction sequence. Thus, artifacts that were produced during the beginning of a reduction sequence will be quantitatively and qualitatively different from later stage artifacts (Braun, et al.,

193 2008; Douglass, et al., 2015; Toth, 1985). This phenomenon increases the chances of

Type I errors (false positive) in which two Paleolithic assemblages may be considered

technologically different, when in reality they are technologically similar, and the flakes

derive from different points along the reduction continuum. For example, artifacts

produced by the same knapper from the Chapter 2 experiments exhibited statistically

different external platform angles, but the two ‘assemblages’, differed only in their place

in the reduction sequence. This example demonstrates how aggregating stone tools and

studying only end-product form is problematic. It is therefore necessary to control for reduction intensity—the degree to which a stone has been reduced—in any comparative lithic analyses.

A.2. Previous Cobble Reduction Experiments

It has been postulated that a flake’s relative position in a sequence of removals will reflect its reduction intensity. Sequence number is defined by the number of prior flake removals from the core (number of prior removals + 1). Because archaeological stone tools are part of larger palimpsests in which true sequence number is impossible to know, it is necessary to infer a flake’s stage in the reduction sequence through post-hoc analysis of flake attributes. This problem is perfectly suited for middle-range research, in which cobble reduction experiments replicate flintknapping sequences, and the experimentally produced flakes are analyzed to determine which proxies best predict sequence number.

Previous experiments by Toth (1985) suggest location of cortex as a predictor of sequence number and created six technological flake categories (Table A-1).

Table A-1. Technological Flake Categories described by Toth (1987).

Cortical Platform Non-cortical Platform

194 Full Dorsal Cortex I IV Partial Dorsal Cortex II V No Dorsal Cortex III VI

Figure A-2. Technological Flake Category as defined by Toth (1987). However, later work by Braun (2008), using Oldowan reduction methods, demonstrated that Toth’s technological flake category is subject to effects of initial core size. Large nodules have higher surface area and produce a higher percent of Type I, II, and III flakes whereas smaller nodules with low surface area have more non-cortical flakes. Braun used linear regressions and linear mixed models to better predict sequence number using multiple flake measurements. This resulted in a mixed model with significant results (Braun, et al., 2008: 2158).

Tool manufacture, as any flintknapper will confess, is rarely a straightforward continuum, but rather a winding path of irregular turns, in which the knapper is consistently responding to changing geometric and raw material constraints. The ways in which the knapper responds to or manipulates these nodule geometries can be conceptualized as the core reduction strategy, the methods that the knapper uses to

195 continuously remove flakes. A core reduction strategy, as used here, therefore refers to the pattern of flake removals and does not make reference to the planning capabilities or

‘mental templates’ of Paleolithic knappers.

A past knapper’s core reduction strategy can be gleaned through re-fitting studies and several different patterns have been identified through these studies. Bifacial reduction involves the systematic removal of flakes from two faces, such that the flake removal of one face serves as the striking platform for a removal from the opposite face on the same edge. Bifacial flaking is common to handaxe production and point retouch.

Levallois (aka prepared core) is another core reduction strategy in which the cobble is comprised of two faces, such that one face is steeper, serving as a striking platform, and the other surface is used continuously for flake removals (Boëda, 1995). In both bifacial and Levallois reduction, some degree of convexity maintenance is required. Because one face is preferentially flaked relative to the other in Levallois reduction, the latter face inevitably has more cortex upon discard.

While the prediction model from Braun et al (2008) provided an accurate way to bin Oldowan assemblages according to reduction intensity, it is not clear how technological variables behave under non-Oldowan reduction methods like bifacial and

Levallois reduction. In other words, it is not clear how a knapper’s core reduction strategy may impact the variables used in the prediction model. Specifically, given that

Levallois is geometrically a different reduction approach (Boëda, 1995), it is unclear if

Braun’s (2008) model accurately predicts sequence number in such a prepared core assemblage. It is hypothesized here that bifacial and Levallois reduction methods will differentially affect lithic attributes previously associated with sequence number in

196 studies of Oldowan reduction methods (e.g. cortex, number of flake scars) such that the accuracy of these previous models will be decreased in assemblages dominated by bifacial and Levallois reduction.

A.2.1. Methods

Reduction experiments were conducted to understand prepared core and bifacial

knapping mechanics and how they influence technological variables across reduction

sequences. Standardized porcelain nodules were used to prevent effects of size and shape as documented by Braun et al (2008). See Chapter 2 for information regarding the mechanical properties and manufacture of the porcelain nodules. To prevent effects from variation in skill, only one knapper created the experimental assemblages (Dr. Nada

Kreisheh). The knapper used one hammerstone throughout the experiment. To determine if core reduction strategy affects the accuracy of lithic attributes to predict sequence number prediction, half of the reductions used the Levallois reduction method and half used bifacial reduction used in handaxe production. The knapper was not told when to stop knapping, and she flaked each nodule to exhaustion. For each reduction set, sequence number was recorded for every flake. Flakes were removed from the debitage pile as knappers continued knapping so as not to disturb the knapping process (Keller and

Keller, 1996). All complete flakes were recorded regardless of size. If two or more flakes were removed at the same time they received the same sequence number with a suffix

(e.g. 3a, 3b, 3c).

197 Table A-2. Complete flakes (including preferential Levallois flakes) measured in the reduction experiment.

Session ID Number of Flakes Type 1 15 Bifacial 2 14 Levallois 3 14 Levallois 5 16 Bifacial 6 17 Bifacial 7 15 Levallois 8 19 Bifacial 10 15 Levallois 11 20 Bifacial 13 15 Levallois Total 160

Complete flakes (n=160) were measured with Mitutuyo digital calipers. See Table A-3

for the variables measured.

Table A-3. Variables measured in reduction experiment.

Variable Description Sequence Number The number of prior flakes removed from the core (number of prior flakes + 1) Technological Flake Category See Toth (1985). Flake Length Maximum dimension of the flake. Flake Width The maximum width of the flake, perpendicular to the axis of maximum length. Flake Mass Mass of the flake in grams. Dorsal Scar Count The number of flake scars larger than 1 cm in maximum dimension on the dorsal surface. Dorsal Cortex The percentage of cortex present on the dorsal surface, represented by a code (see Table A-4). A.2.2. Analytical methods

Because each sequence is a different length, relative sequence number was calculated by dividing raw sequence number by the length of the total sequence. This provides a means

to compare linear regressions of sequence number across multiple reduction sequences of

differing lengths. To account for effect of flake size on scar count, dorsal scar count was

198 divided by the log of the flake area. This created the normalized scar count (NSC).

Finally dorsal cortex was measured as: 0%, 1-20%, 21-40%, 41-60%, 61-80%, 81-99% and 100%. These values were subsequently coded (Table A-4).

Table A-4. Cortex scores.

% Score Cortex 0 7 1- 20% 6 21-40% 5 41-60% 4 51-80% 3 81-99% 2 100% 1

To explore the predictive power of the tested variables and relative sequence number in archaeological analyses, correlations were tested at three levels of aggregation: i) pooled assemblage scale (n=160) ii) pooled Levallois (n=73) and pooled Bifacial flakes

(n=87) and iii) individual reduction sequence (n=14-20). Normality tests were conducted on all variables at all scales. To test these relationships requires non-parametric tests at all scales.

A.2.3. Multivariate analysis

Several multivariate approaches were used to test the power of the combined variables to predict reduction stage of the flakes. These approaches included: multiple linear regressions, principal coordinates analysis using a Gower matrix, and discriminant function analysis.

Multiple linear regressions are robust against non-normal distributions if samples vary homogenously and are of sufficient size (Ellison and Gotelli, 2004). Three scales

199 were tested: pooled data, bifacial reduction data (n=87), and Levallois data (n=73).

Sample sizes of individual reduction sets are too small to accurately model with multiple regression analysis. All three models were tested using all of the characters, and subsequently with characters of significant effect (p <0.001).

Principal coordinates analysis was used on a Gower difference matrix which is suited to the multiple data types (ordinal and ratio scale variables) studied here.

A.3. Reduction Experiment Results

A.3.1. Correlation tests

To test predictive power of the variables against relative sequence number, bivariate correlation tests were conducted (Table A-5). All variables show a correlation with relative sequence number and all are significant to the p <0.01 level. Within bifacial reduction reduction, the strongest predictor of relative sequence number is technological flake category followed by cortex and normalized scar count. This is in accordance with the results of Braun et al 2008, which only test Oldowan reduction methods. Within

Levallois reduction, however, all predictors are equally weak. When comparing correlation of Levallois and bifacial reduction strategies, the three flake size attributes

(flake mass, flake length, and flake width) exhibit similar correlations between the two reduction strategies. Cortex, scar count, and technological flake categories were substantially weaker predictors in Levallois reduction compared to bifacial reduction.

200 Table A-5. Correlation coefficients at the level of reduction strategy.

Braun et al Attribute Bifacial Levallois 2008 Technological Flake Category r = 0.45 Tau = 0.645 Tau = 0.377 Log(Flake Length) r = -0.10 Tau = -0.411 Tau = -0.332 Log(Flake Width) r = -0.17 Tau = -0.328 Tau = -0.248 Log(Flake Mass) r = -0.14 Tau = -0.354 Tau = -0.311 Dorsal Scar Count r = 0.54 Tau = 0.383 Tau = 0.336 Dorsal Scar Count / log(Flake r = 0.65 Tau = 0.433 Tau = 0.364 Length x Flake Width) Log (Cortex Score) r = 0.47 Tau = 0.585 Tau=0.265 Cortex Score / log ( Flake Length r = 0.62 Tau = 0.559 Tau = 0.244 x Flake Width)

Table A-6 shows correlation coefficients at the level of two individual reduction sets, sessions 10 and 11 as an example of one Levallois and one bifacial reduction set.

Correlation coefficients for all other reduction sets are listed in Table A-11. Session 10 is a Levallois reduction and session 11 is a bifacial reduction. Technological flake category is the strongest predictor for both sessions, followed by cortex score, normalized cortex score and normalized scar count. Session 11 and Session 10 show similar correlations for all tested variables.

Table A-6. Correlation coefficients at the level of individual reduction sets 10 and 11.

Session 11 – Session 10 – Attribute Bifacial Levallois Tau = 0.76 Tau = 0.50 Technological Flake Category p < 0.001 p = 0.02 z = 4.35 z = 2.38 Tau = -0.51 Tau = -0.49 Log (Flake Length) p < 0.01 p = 0.01 T = 47 T = -0.49 Tau = -0.42 Tau = -0.31 Log (Flake Width) p = < 0.01 p = 0.11 T = 55 T = 36 Tau = -0.47 Tau = -0.37 Log (Flake Mass) p < 0.01 p = 0.06 T = 50 T = 33

201 Tau = 0.32 Tau = 0.40 Dorsal Scar Count p = 0.07 p = 0.05 z = 1.82 z = 1.92 Tau = 0.36 Tau = 0.43 Dorsal Scar Count / Log (Flake Length x p = 0.03 p = 0.03 Flake Width) T = 129 T = 75 Tau = 0.73 Tau = 0.34 Cortex Score p < 0.001 p = 0.09 z = 4.27 z = 1.67 Tau = 0.73 Tau = 0.35 Cortex Score / Log (Flake Length x Flake P < 0.001 p = 0.07 Width) T = 167 T = 71

A.3.2. Multivariate analysis results

Bifacial – When all characters are used without any interaction terms, adjusted r2

= 0.70, residual standard error = 0.14, DF = 80, F-statistic = 36.23, and p < 0.001. If only

the variables with significant p-values (Technological flake category, flake length, and normalized scar count) are used in the model, adjusted r2 = 0.68 and residual standard

error = 0.14, DF = 83, and p < 0.001, similar to the previous model with all the variables.

Levallois – When all characters are used without any interaction terms, adjusted r2

= 0.44, residual standard error = 0.18, DF = 66, F-Statistic = 10.41, and p < 0.001. Unlike

in the bifacial reduction model, in the Levallois model technological flake category was

not a significant predictor. When only variables with significant p-values are used in the

model, adjusted r2 = 0.46, residual standard error = 0.18, DF = 69, F-statistic = 21.05, and p < 0.001. In this case, the added variables explain more of the variation in sequence number.

Pooled data – When all characters are used without any interaction term, adjusted r2=0.52, residual standard error = 0.17, DF = 153, F-statistic = 29.55, p < 0.001. When

only variables with significant p-values (technological flake category, normalized scar

202 count, and flake length) are included, adjusted r2 = 0.52, residual standard error = 0.17,

DF = 156, F-statistic = 58.64, p < 0.001.

Table A-7. Bifacial reduction linear model with all variables.

Predictor Estimate Std. Error t value Pr(>|t|) log (Flake Width) -0.11 0.12 -1.10 0.28 Normalized Cortex -0.03 0.10 0.27 0.79 Technological Flake 0.07 0.02 3.30 < 0.01 Category Normalized Scar Count 0.26 0.09 2.78 < 0.01 log(Flake Mass) 0.08 0.05 1.55 0.12 log(Flake length) -0.32 0.13 -2.45 0.02 (Intercept) 1.71 0.52 3.30 < 0.01

Figure A-3. Bifacial reduction multiple linear regression observed sequence number versus predicted sequence number.

203 Table A-8. Bifacial reduction multiple linear regression when only significant values used.

Predictor Estimate Std. Error t value Pr(>|t|) Normalized Scar Count 0.26 0.09 2.76 < 0.01 log(Flake Length) -0.20 0.93 2.76 < 0.001 Technological Flake 0.07 0.01 5.37 < 0.001 Category (Intercept) 1.01 0.18 5.41 < 0.001

Figure A-4. Levallois multiple linear regression observed sequence number versus predicted sequence number. Table A-9. Levallois multiple linear regression.

Predictor Estimate Std. Error t value Pr(>|t|) log(Flake Width) 0.39 0.15 2.64 0.01 Normalized Cortex -0.12 0.14 -0.82 0.41 Technological Flake 0.03 0.03 0.99 0.33 Category Normalized Scar Count 0.43 0.12 3.47 < 0.001 log(Flake Mass) -0.21 0.07 -3.04 < 0.01 log(Flake Length) -0.01 0.18 -0.04 0.97 (Intercept) -0.39 0.76 -0.51 0.61

204

Figure A-5. Pooled prediction model.

Table A-10. Multiple linear regression for pooled data.

Predictor Estimate Std. Error t value Pr(>|t|) log (Flake Width) 0.13 0.09 1.44 0.15 Normalized Cortex 0.04 0.08 0.51 0.61 Toth type 0.05 0.02 2.43 0.02 Normalized Scar Count 0.32 0.08 3.94 < 0.001 log(Flake Mass) -0.03 0.04 -0.67 0.50 log(Flake Length) -0.25 0.11 -2.20 0.03 (Intercept) 0.87 0.46 1.90 0.06

205

Figure A-6. Technological Flake Category versus square root of relative sequence number.

A.4. Reduction Experiment Discussion

This reduction experiment confirms the finding in Braun et al 2008 that linear

relationships exist between relative sequence number and the variables studied (listed in

Table A-3). Unlike Oldowan reduction methods, however, bifacial and prepared core

reduction incurs volumetric changes that are not as adequately captured in a multiple

linear model.

Correlation tests show strongest predictive power of the variables when the scale

is reduced to individual reduction sets. The correlative relationships are similar for both

Levallois and bifacial reduction strategies at the level of individual reduction sets

(Sequence 10 and Sequence 11) (Table A-6). The strongest predictor of both reduction sets is technological flake category (Levallois Tau = 0.50, bifacial reduction Tau = 0.76), followed by cortex score, and normalized cortex.

206 The stronger correlations exhibited at individual reduction sets are likely due to

decreased noise; both the variation in knapper skill and variation in individual nodule

flaking mechanics is muted at this scale. Each reduction sequence is a unique trajectory

of flaking events in which one event is shaped by the previous event. Thus the effects of

reduction are cumulative. If a knapper encounters a flaw in material early on, or

accidentally removes more mass than desired, the subsequent flakes will reflect this

process. This cumulative variation is compounded at the pooled aggregate scale, but is

decreased at the level of individual reduction sets. However, the goal is archaeological

application, and individual reduction sets dating to the eastern African Late Pleistocene

are almost nonexistent. Thus, while it is necessary to understand flaking mechanics at this

small scale, it is necessary to then apply these results to create models that are attuned to

more aggregate scales of variation. In sum, the individual reduction sets indicate that

technological flake category is a strong predictor of sequence number, as are cortex score and normalized cortex, and their utility at more aggregate scales should be further tested.

To better understand how these processes are reflected at more aggregate scales, multiple linear analysis at the level of pooled bifacial reduction flakes, pooled Levallois flakes, and pooled combined flakes was conducted. The strongest linear model occurred in the bifacial reduction assemblage (Figure A-3, adjusted r2: 0.71). In the bifacial

reduction model, the variables with significant p-values are: NSC, log-transformed

Technological Flake Category, and logged Flake Length.

In the Levallois prediction model (Figure A-4), the variables with significant p- values are logged Flake Mass, logged Flake Width, and NSC. However, the distribution of size variables, such as Flake Mass and Flake Width, are susceptible to changes in

207 initial nodule size. Because this experiment used nodules of a standardized size, Flake

Width and Flake Mass were not subject to this variation. In an archaeological

assemblage, however, the initial nodule size is unknown and almost certain to be

variable. Thus the most reliable predictor of sequence number in a prepared core

assemblage is NSC.

There are important differences in the linear models of the Levallois and bifacial

reduction assemblages. Unlike in the bifacial reduction assemblage, for the Levallois

assemblage Technological Flake Category was not a significant predictor (p = 0.085).

Therefore the relationship of cortex across the reduction sequence in a Levallois sequence

is such that the utility of the technological flake category may need revision. Cortex, scar

count, and technological flake categories were substantially weaker predictors in

Levallois reduction compared to bifacial reduction.

These results have direct archaeological application. First, the reduction experiments show that prepared core reduction sequences exhibit patterns of cortex and other variables that are different from those exhibited by Oldowan reduction methods.

This serves as a cautionary tale when applying variables like cortex ratio to assemblages where prepared core methods were used. The reduction experiments also show that

Normalized Scar Count is a strong predictor of reduction stage in prepared core assemblages.

A.5. Supplemental Information

Table A-11 shows correlation results for each individual reduction set.

208

Table A-11. Correlation coefficients at the level of individual reduction sets.

Attribute Session 1 2 3 5 6 7 8 13 Reduction Strategy Bifacial Levallois Levallois Bifacial Bifacial Levallois Bifacial Levallois Tau = 0.77 Tau = 0.62 Tau = -0.15 Tau = 0.63 Tau = 0.63 Tau = 0.56 Tau = 0.59 Tau = 0.28 Technological Flake p < 0.001 p = 0.005 p = 0.51 p < 0.01 p < 0.01 p < 0.01 p < 0.01 p = 0.20 Category z = 3.67 z = 2.81 z = -0.66 z = 3.22 z = 3.29 z = 2.69 z = 3.21 z = 1.31 Tau = -0.58 Tau = -0.49 Tau = -0.08 Tau = -0.38 Tau = -0.43 Tau = -0.54 Tau = -0.32 Tau = -0.31 Log(Flake Length) p = 0.002 p = 0.01 p = 0.75 p = 0.04 p = 0.02 p < 0.01 p = 0.06 p = 0.11 T = 22 T = 23 T = 42 T = 37 T = 39 T = 24 T = 58 T = 36 Tau = -0.18 Tau = -0.38 Tau = 0.08 Tau = -0.43 Tau = -0.38 Tau = -0.50 Tau = -0.13 Tau = -0.26 Log(Flake Width) p = 0.38 p = 0.06 p = 0.75 p = 0.02 p = 0.03 p < 0.01 p = 0.49 p = 0.20 T = 43 T = 28 T = 49 T = 34 T = 42 T = 26 T = 75 T = 39 Tau = -0.40 Tau = -0.55 Tau = 0.03 Tau = -0.45 Tau = -0.44 Tau = -0.52 Tau = -0.11 Tau = -0.26 log(Flake Mass) p < 0.04 p < 0.01 p = 0.92 p = 0.02 p = 0.01 p < 0.01 p = 0.53 p = 0.20 z = -2.03 z = -2. 74 T = 47 T =33 T = 38 z = -2.68 T = 76 T = 39 Tau = 0.40 Tau = 0.21 Tau = 0.19 Tau = 0.30 Tau = 0.56 Tau = 0.49 Tau = 0.43 Tau = 0.27 Dorsal Scar Count p = 0.06 p = 0.34 p = 0.38 p = 0.12 p < 0.01 p = 0.02 p = 0.02 p = 0.19 z = 1.92 z = 0.96 z = 0.88 z = 1.56 z = 2.98 z = 2.44 z = 2.42 z = 1.30 Dorsal Scar Count / Tau = 0.43 Tau = 0.30 Tau = 0.21 Tau = 0.33 Tau = 0.66 Tau = 0.52 Tau = 0.39 Tau = 0.31 log(Flake Length x p = 0.03 p = 0.16 p = 0.33 p = 0.08 p < 0.01 p < 0.01 p = 0.02 p = 0.11 Flake Width) T = 75 T = 59 T = 55 T = 80 T = 113 T = 80 T = 119 T = 69 Tau = 0.69 Tau = 0.45 Tau = -0.01 Tau = 0.60 Tau = 0.63 Tau = 0.41 Tau = 0.45 Tau = 0.23 Cortex Score p < 0.001 p = 0.04 p = 0.95 p < 0.01 p < 0.01 p = 0.05 p = 0.01 p = 0.26 z = 3.34 z = 2.10 z = -0.06 z = 3.04 z = 3.21 z = 1.99 z = 2.54 z = 1.12 Cortex Score / log ( Tau = 0.73 Tau = 0.52 Tau = 0.01 Tau = 0.53 Tau = 0.44 Tau = 0.39 Tau = 0.40 Tau = 0.16 Flake Length x Flake P < 0.001 p < 0.01 p = 1 p < 0.01 p = 0.01 p = 0.05 p = 0.02 p = 0.43 Width) T = 91 T = 69 T = 46 T = 92 T = 98 T = 73 T = 120 T = 61

209

Appendix B. Additional Study Localities

The goal of this appendix is to build a systematic review of one small set of MSA

assemblages, focusing on eastern Africa, quantifying not only form but technological

process. This section reviews the background and history of research at each study

locality. In most cases, archaeologists who are no longer living excavated the

assemblages studied. This section therefore provides necessary context to the

assemblages of study. There are several factors to consider when choosing archaeological

assemblages for study. The most important, as Anthony (1978) pointed out, is

considering the purpose that the archaeological data will serve, and ensuring the

assemblage in question will serve that specific purpose. This dissertation sought to study

technological process, with a focus on core technology, and therefore a high core

frequency was an initial consideration.

Next, one considers the ecological, geographical, and temporal context of the assemblage. The sites studied here focus on eastern African, particularly Kenya and

Tanzania. Only sites with established “MSA” technological components were considered.

The temporal context varies across each site and is discussed in detail later. Sites with relatively long stratigraphic sequences were prioritized. Some attempt was made to control for different ecological contexts, particularly with regard to elevation, annual precipitation, and aridity although further work on paleonvironmental reconstruction is sorely needed. Finally, analogous analytical units were created by studying assemblages with common raw material, or at the very least, similar flaking mechanics.

Finally, perhaps the most important but rarely mentioned factor contributing to archaeological analyses is logistics. Research permits, varying curation standards, local

210 safety concerns, and funding are all external factors that ultimately determine the

directions in which research progresses. A poignant example is that of Harry Merrick, a

student of Glynn Isaac, whose original dissertation plan was to study Apis Rock (now

Nasera), but whose plans were foiled due to a hold up of research permits with the

Tanzanian government. He instead had to shift to Kenya to study MSA and LSA sites at

the NMK, excavating Lukenya Hill instead; Mehlman, a student of C. Keller, later

excavated Nasera in 1975-1976.

Similar logistical issues arose with this dissertation. Assemblages housed in the

NMK are particularly well accessioned, the research permits easily obtained, and study

conditions very favorable. Thus the majority of these data were collected there. Sally

McBrearty kindly provided permission to study the Muguruk assemblage. Analysis of the

Lukenya Hill assemblage began in 2013, at which time Christian Tryon began re-dating

the OES of the GvJm22, and re-analyzed the lithic assemblage with Ravid Ekshtain.

Research at Koobi Fora, in conjunction with the Koobi Fora Field School began in 2013;

J. W. K. Harris and David Braun provided access to Alison Kelly’s assemblages at the

NMK in 2014. The initial study of these assemblages led to the expansion of Kelly’s

MSA research in the region, which is ongoing. In the beginning of 2015, Christian Tryon

and Jason Lewis invited the author to collaborate at the NMT on the Kisese II

assemblage. Finally, Mehlman’s Nasera collection at Mary Leakey’s Camp at Olduvai

Gorge, was studied. This was by far the most logistically challenging collection to study

and would have not been possible without Dr. Fidelis Masao’s advice and assistance.

For the reasons mentioned above, the study sites included in this dissertation had several limitations. First, several sites had to be excluded for logistical or accessibility

211 issues. Second, raw material variability exceeded expectations at these localities,

especially the large quartz component of the northern Tanzanian assemblages. There is a

silver lining, however, as such raw material diversity has resulted in novel analyses.

Despite original interests in Levallois origins and the early MSA, with the exception of

Muguruk, it is likely that these assemblages span the later MSA and the MSA-LSA

transition. This too has a silver lining, as these sites are more easily dateable with radiocarbon methods, building a framework on which future dating work can be undertaken.

Any one individual’s attempt at an “exhaustive” study of technology of the East

African MSA is primed for failure, as a single individual simply cannot study every lithic spanning the vast geographic space or time represented by the MSA. Rather, this study builds on the Herculean dissertations of Merrick (1975), Anthony (1978), McBrearty

(1986), Mehlman (1989), and Kelly (1996). Furthermore, it has been influenced by ongoing work in southern Tanzania and Olorgesailie with Alison Brooks and John

Yellen, at East Turkana with David Braun and Jack Harris, and at Kisese II with

Christian Tryon. A regional understanding of technology requires an army of archaeologists, and artillery comprised of numerous, carefully excavated sites.

212

Figure B-1. Study localities described in the text.

213 B.1. Muguruk

Muguruk (-0.084°, 34.633°) is located in Kisumu district, western Kenya. Archdeacon

Walter Edwin Owen originally surveyed the area in late 1936 and coordinated analysis with L.S.B. Leakey (Leakey and Owen, 1945). A single trench was excavated by Alex

Opira-Odingo in 1978 and is accessioned at the NMK under KNM 2502. Opira-Odingo’s

findings are unpublished and contextual information for his excavated materials is not

available at the NMK. In 1979-1981 Sally McBrearty carried out excavations as part of

her doctoral dissertation (KNM 2501). Her findings are reported in her thesis (McBrearty,

1986) and in McBrearty (1988).

Figure B-2. Muguruk stratigraphy from McBrearty (1988). McBrearty defined the artifact-bearing sediments at Muguruk as the Muguruk

Formation, sub-divided into six members. The formation overlays a basal unit of Ombo phonolite. Above this, Member 1 consists of conglomerate. Member 2, in which the

OjollaIndustry artifacts are found, is a coarse to medium sand. Member 3 is a mudcracked gray clay and has very few artifacts. Member 4 is considered lateritic (red clayey sands) and contains dense artifacts of the Pundo Makwar industry. In the southern

214 part of the site the conglomerate (Member 1) is overlain by a calcareous channel with a

U-shape at the base, suggesting rapid erosion. This channel, Member 5, is very well sorted and cross-bedded, with calcite nodules at the base. Member 5 is overlain by buff silts and sands at the top of which is a dense concentration of MSA artifacts. According to McBrearty, it is possible that Member 6 is a lateral continuation of Member 3, and this

is in agreement with the Owen and Leakey report. McBrearty also reports potential

termite mixing in Member 4 (McBrearty, 1990).

Previous Muguruk Lithic Studies

Leakey and Owen (1945) originally describe two lithic technological industries at

Muguruk. They ascribed the lowermost artifacts to the lower Tumbian and considered

Muguruk to be the type-site of the Tumbian. They ascribed artifacts from the upper part

of the section to the Levalloisan industry. Similarly, McBrearty defined two separate

industries, and named the lowermost artifacts in Member 2 the Ojolla industry, and those

from the upper channel sands and red sands as the Pundo Makwar industry. Generally

speaking, the artifacts from Member 2 are considered Sangoan-Lupemban (sensu Clark

(1988)), or transitional between Acheulean and MSA. The most unique component of the

Muguruk locality is what McBrearty called Lupemban lanceolates: elongated bifaces

which are unique relative to other bifaces in their uniform thinness. The upper sequence

is considered general MSA. : There are no chronometric dates for the Muguruk materials

but Tryon and Faith (2013) suggest 170-10 ka based on calculated sedimentation rates.

Muguruk Reanalysis Results

As McBrearty writes in her field notes, “All artifacts are of Ombo phonolite,

unless otherwise noted.” Indeed phonolite comprises the majority of the assemblage,

215 although there is a finer Kisumu phonolite in some cases. There is no indication that the

collection is selected or biased, as McBrearty reports the use of a ¼-inch sieve. She recorded the x, y, z coordinates of all pieces. These coordinates are available in the catalogue book available at the NMK and are relative to a local datum. The assemblage is organized into trays typologically and according to Member. Artifacts from the

Lanceolate Trenches were the focus of this analysis. McBrearty separated the lanceolates, core axes, and other illustrated pieces; these artifacts were not part of the formal lithic analysis, which focused on complete flakes and cores.

Flakes

The flakes are in various stages of weathering which makes it sometimes difficult but not impossible to discern cortex. According to normalized scar count, the flakes span the earlier, middle, and later part of the reduction sequence (Figure B-3). A Shapiro Wilk test indicates the NSC distribution is normally distributed, indicating that the highest proportion of flakes are from the middle of the reduction sequence. Faceted and dihedral platforms are present (14% of the studied sample). Flake scars are discernible but directionality often is not. Due to weathering stage, no data was recorded on use wear or edge damage, although McBrearty did consider many of the pieces ‘utilised’.

216

Figure B-3. Reduction Intensity Distribution of Muguruk Assemblage The majority of the complete flakes exhibit dorsal preparation and isolation of the platform, usually in the form of reduction of overhang resulting in small dorsal step or hinge terminations on one or both sides of the point of impact. The most common flaking strategy is radial, although bi/unidirectional is also present, particularly convergent.

Larger, thick pieces are present, and are almost entirely cortical which were possibly removed to quickly de-cortify the cobble and remove flaws of the raw material. Also some core edge flakes are present. Overall the flakes demonstrate isolation of platforms and core maintenance.

Some of the flakes show flake scars that fit blade dimensions, having very parallel sides. This was confirmed by later analysis of tray #27, in which many of the flakes themselves exhibit parallel edges and fit the blade definition having length twice the width. This was quantified using an assemblage-specific blade cutoff in which elongation index for the entire assemblage was calculated and only flakes with the highest

217 elongation index were considered ‘blades’. (Tixier, 1963). Figure B-3 shows the

Elongation Index (maximum length/maximum width) as three equal bins. The line y=2 represents the traditional blade cutoff of flakes having a length dimension twice of the width. Five flakes fall below this line. Importantly, there are more light blue flakes, representing the flakes with the highest elongation index values that lie above this line.

This indicates an elongated flake component is present in the assemblage. These “flake blades” exhibit variable curvature and include some core edge, or crested, blades. Most are radial or bi/unidirectional with parallel arises. McBrearty 1988 makes no mention of blade, blade production, or laminarity in her discussion of the Ojolla Industry from

Member 2. This analysis, however, suggests some degree of blade production.

Figure B-4. Muguruk elongation index binned into tertiles.

218 B.2. Prospect Farm

Prospect Farm is located on the slopes of Mount Eburru near Lake Elementeita, and was named after the farm on which it was found. Locality I was excavated in 1963 in a period of six weeks by Barbara Anthony and Glynn Isaac. They first travelled to Eburru on advice from L.S.B. Leakey in search of “Stillbay” artifacts reported on the surface by the farm’s owner. While surveying the area around Locality I in the evenings, Anthony discovered more artifacts eroding from deposits further down the escarpment. It was at this locality that they opened a new excavation, with the assistance of Ron Clarke, which they called Locality II. The Locality II excavation quickly eclipsed Locality I in terms of time devoted to the excavation and the amount of excavated material. During this time

Glynn Isaac went to Lake Natron, and Anthony continued excavating Locality II until

July 1964 (Anthony, 1978).

Stratigraphy is described in detail in Anthony’s thesis and in Isaac (1969).

Locality I was excavated in spits of uneven thickness, following changes in geology.

Locality II was excavated in a series of steps, which roughly corresponded to “floors”, as identified by Anthony, with a particular aim to understand the chronology from the

“Kenyan Capsian” to the “Stillbay”. Anthony divided material from the Prospect Farm excavation into four phases: Phase I as the oldest and Phase IV the youngest. She provides little geological or technological reasoning for what defined the boundaries of her phases, and admits that other horizons likely exist between her described “phases”.

As such Anthony’s Phase were not considered in my analysis, and I recorded spit number as the most specific form of contextual information.

Merrick (1975) also studied the Prospect Farm materials. His analysis took place prior to the completion of Anthony’s thesis, preventing his study of the excavating team’s

219 geological profiles and definitions. As such, Merrick designed his study according to stratigraphy published by Anthony in 1967 (Anthony, 1967), which divided the materials into 5 archaeological horizons. The lower 4 of these horizons were stratified deposits within the Prospect Farm Formation while the uppermost horizon was considered Kenyan

Capsian, with charcoal from this layer dated to 10.6 ka. Merrick studied only material from Locality I, probably because Anthony’s own analysis had focused heavily on

Locality II and she had little quantitative data from Locality I. Due to low artifact density,

Merrick assigned spits 9-23 based on their archaeological horizon, sample 1, sample 2 spit 16, and sample 3 (lower two based on affinities of “Stillbay horizon”).

Figure B-5. Map of Prospect Farm from Anthony (1978). Chronologically, dating attempts were made but remain speculative. Michels

(1983) used obsidian hydration and concluded that artifacts deriving from Phase I could not be dated as they were too weathered. Phase 2 consisted mostly of heavily spalled

220 surfaces beneath which remnant hydration rims yielded dates ranging 24.5-14.7 ka while

some specimens had unspalled remnants dated 81.8-88.4 ka. Phase III was the most

successful for Michels dating attempts and suggested three occupations, the first between

stratum 9 and 10 at 120 ka. Second, stratum 9 “capped by a well-developed fossil soil”,

dates 106.3-108.6 ka. But the unspalled remnants yielded 14.9-18.3 ka. Michels argues

these unspalled areas appear less extensively weathered and are more accurate than those

in Phase 2. The third period in Phase III consists of 35cm of colluvium and dates 46.5-

53.1 ka. Phase IV dates 46.7-53.6 ka, almost identical to Phase III.

0 Phase I Phase II Phase III Phase IV

Discoidal Levallois Total Surface Single Surface Multifacetted Unstruck (non-Levallois)

Figure B-6. Core reduction strategies reported by Anthony (1978) from oldest to youngest layers. Anthony considered flake scar counts and most core measurements uninformative. Instead, her analyses focused on technological descriptions of core reduction strategies. As such, she described a unique core reduction strategy that she referred to as the “Total Surface Core”:

221 “The Total Surface Core Method starts off with the concept that the flake can be determined by the form of the perimeter or circumference of the core from which it is removed and not by the false circumference created by the location and depth of surface trimming scars. The core is thus trimmed vertically around the sides of the core to give it the proper shape. A flake is then struck off the upper surface in such a way that it removes the whole surface; it will, of course, have the same form as that of the core in plan view. It is a very much simpler method of predetermining the form of the flake removed than is the Levallois Method.” (Anthony 1978:32)

Figure B-7. Sketch of ‘total surface core’ reduction pattern described by Anthony (1978). Anthony reports a total lack of bipolar reduction, and absence of bidirectional flaking. She argues that the cores were so exhausted that a formal typology was useless, as one core may typologically be a discoid but was once a Levallois core. Her analysis thus focused on process of reduction, as she argued, “a knowledge of customs and process is important, inasmuch as they represent a body of cultural behavior of past peoples…” (Anthony 1978:33).

Surprisingly, when Anthony begins to discuss Locality I and the beginning of

Phase III, she describes a terrible mix up that occurred at the NMK: while she spent four years analyzing the material from Locality II, the artifacts from Locality I were never

222 actually sorted into cores or tools and never received computer punch cards. She admits

that her analysis of the material of Locality I (Phase III and IV in particular) was very

haphazard as she spent four years focusing on the Locality II assemblage. As such, the results presented here may represent the first systematic study of Locality I.

Prospect Farm Analysis Results

All of the artifacts in the dataset presented here derive from Locality I, the first of

Anthony’s excavations, Spits 19-23. Anthony ascribes this material to Phase III and

Phase IV. The measured pieces are reported in Table B-1. Only complete flakes were

measured. Highly weathered pieces, in which dorsal and ventral sides are

indistinguishable, were not measured. Qualitative study of these flakes, and particularly

of incomplete flakes, was conducted with the objective to understand core reduction

strategies.

Raw material throughout the sequence is almost entirely obsidian. Highly

ferruginized nephelinite is present in small percentages as well as coarse-grained

quartzite, possibly the result of rock fall. For example some pieces are heavily striated

while others exhibit metallic or glassy luster. Future XRF study of the Prospect Farm

obsidian is needed. Unfortunately advanced chemical weathering disproportionately

affected nephelinite artifacts. This was also seen on the alkali-volcanic materials at

Muguruk. As a result, technological information (directionality, platform preparation,

retouch) was not easily discernible on most nephanalite pieces and very few nephelinite

pieces were measured here. This analysis therefore focuses on the obsidian component

and the raw material frequency of the dataset is not representative of the larger spits in

which they were excavated.

223 Technologically, Spits 19-23 at first glance resembles a typical “LSA” assemblage. Retouched pieces were common, although not systematically studied in this analysis, and included backed pieces, points, and various scrapers (side, end, double).

These were categorized by Anthony as MRP (“miscellaneous retouched pieces”) and are detailed in her dissertation. Proximal fragments exhibited dorsal trimming of the platform overhang, often combined with chapeau de gendarme (Inizan, et al., 1999) platform morphology. Levallois cores, defined by having two hierarchical surfaces, were rare, comprising only 3 of the 26 measured cores.

The most technologically unique aspect of the Prospect Farm assemblage is the presence of what Anthony referred to as “total surface cores”. Merrick did not describe these, but he did mention “oval scrapers” as a unique component of his Sample 1.

Table B-1. Prospect Farm Measured Lithic Dataset

Blade Complete Flake Retouched Spit Core Grand Total BladeFrag Flake Frag Piece 19 1 11 5 3 20

20 12 2 2 17

21 1 10 9 20

22 2 9 2 13

23 1 5 1 5 12

Total 3 43 26 7 9 89

B.3. Kisese II

Kisese II (4°29'30.47"S, 35°48'43.31"E) is a painted rock shelter in Kondoa

District of Tanzania with a stratified sequence 6m in length spanning the Late Pleistocene and Holocene. It is located in the Irangi hills of the southernmost portion of the Gregory

Rift Valley and overlooks the Masaai Steppe. Mary and Louis Leakey originally visited

Kisese in 1935, and they excavated the Kisese II locality in 1951, reaching a depth of 4.2

224 meters (Leakey, 1955). Ray Inskeep continued these excavations in 1956 with a 6 m deep

excavation that he divided into 26 spits of approximately equal thickness. Ray Inskeep

published a short overview of his findings, which for the Stone Age deposits focused on

relative frequencies of artifacts with no quantitative measures of lithic attributes (Inskeep,

1962).

In 2015 Christian Tryon radiocarbon dated OES fragments from the Inskeep

excavation, providing a chronological framework for the archaeological material (Tryon

et al, in prep). Lithic analysis by Tryon and myself suggest the presence of bipolar

technology throughout the sequence, with a near absence of Levallois technology after

~35 ka. Ochre use occurs by ~55 ka and OES beads are present by ~37 ka (Tryon et al, in

prep). The lithic assemblage is dominated by quartz, obtained predominantly in the form

of small river pebbles. Faunal remains were studied by Jim Simons after the Inskeep

excavation, and later by Marean for his PhD thesis, and published in Marean and Gifford-

Gonzalez (1991). Both studies report open grassland species, including an extinct pygmy

alcelaphine described by Curtis Marean. Similar fossils were later found at Lukenya Hill,

Katanda, and Lainyamok and the taxon was formally defined as Damaliscus hypsodon in

(Faith, et al., 2012). Several hominin remains were discovered in the excavations, the deposition and morphology of which are still under study.

Both the Leakey and Inskeep Kisese II collections are housed at the National

Museums of Tanzania in Dar es Salaam. The Leakey collections were previously housed

in the National Museum of Kenya in Nairobi, and were repatriated to Tanzania along

with hominin fossils, fauna, and artifacts from Olduvai in 2010. The Kisese II collection

225 is incomplete; Inskeep sent several pieces to Oxford for further analysis, and it is possible

that other pieces were thrown away (Kwekason, pers. comm.).

The assemblage present at NMT is over 99% quartz, including crystalline

varieties, milky macrocrystalline varieties, and quartz with hematite inclusions. Fine-

grained quartzite is also present. Due to the deterioration of the collection, the analyses

presented here are necessarily qualititative. The collection is organized by spit and by

type as defined by Inskeep in his notes (Table B-2).

Table B-2. Inskeep’s Typology

Type Inskeep Description 1 – 8 Unnamed microliths 9 Backed scraper 10 Single backed blade 11 Double backed blade 12 Awl 13 Small convex scraper aka “thumb-nail scraper” 14 Straight edged scraper 15 + 17 Large convex scraper 16 Concave scraper 20 + 21 Point, Unifacial and Bifacial 18 Outils ecaillés 19 Burin 22 Micro core tools 29 Sinew frayer 23 Discoid core 24 Single platform core 25 Bipolar core 26 Amorphous core 27 Two directions from one edge, later called “keeled” 30 Opposed platform core 31 Miscellaneous retouch 32 Adzes

226 Figure B-8. Kisese II Lithic Sequence (from Inskeep archives, scanned by Jason Lewis).

Kisese II Reanalysis Results

The first objective in this Kisese II reanalysis was to determine to what extent the

NMT collection is representative of the original excavated assemblage, to determine

what, if any, quantitative analyses can be carried out. To do this, an inventory of the

collection was created by going through each bag, recording the spit number and Inskeep

type, and counting the lithics present. This exercise provided an opportunity to have an

overview of the technology of the site across the sequence, while studying the different

tool morphologies described by Inskeep in 1956.

A total of 2743 lithics were present at the NMT (Table B-3) including all pieces.

Inskeep reported 5957 total lithics in his archives, including only retouched pieces and cores. Therefore less than 46% of the assemblage is still present at the NMT in Dar es

Salaam.

227 Inskeep’s typology evolved over time. This is important because the only

provenience information associated with the collection is Spit and Type, and artifacts are

bagged accordingly. It is likely that Inskeep carried out lithic analysis according to spit,

and then arranged artifacts by “type”, and bagged them accordingly such that one bag

could have several dozen crescents while another had only cores. However after leaving

Tanzania, likely upon writing the manuscript, he re-arranged his groupings, mostly changing the level of inclusivity of each type. This changing typology made it very difficult to compare Inskeeps’ original count data with that which is present today at the

NMT, to determine the extent of attrition of the assemblage, using only the provenience information and the typology listed in his published work.

It was not until the discovery of the Inskeep archive at the McDonald Institute that his typology could be fully understood in light of the NMT collections. For example in

his earliest typology Inskeep referred to unifacial and bifacial points as Type 20 and 21,

respectfully. But in his later archived notes he combined all points together under Type

16. The same problem persisted for “micro core tools” which were originally called Type

22, then Type 18. To further complicate this, outils écaillées were also Type 18

originally, and later Type 14. After scanning the entire assemblage, and especially by

visually confirming that, throughout the sequence, the pieces that Inskeep labeled Type

18 were definitively outils écaillées, it became clear which of Inskeep’s archives matched

the typology he used for analysis, and thus which tool type corresponded to which

number in the NMT assemblage.

In many occurrences, however, the type label on the bag did not represent the

artifacts inside of the bag. This may be expected in some degree due to the qualitative

228 nature of typologies generally, especially since Inskeep specified 12 kinds of backed

pieces. But it became clear that in fact the problem was far worse than simple inter-

analyst variation. One bag labeled type 18, presumably outils écaillées, included a fossil,

a piece of ochre, and one bipolar core. Another bag, also labeled Type 18, contained 6

outils écaillées, two burins, two bipolar cores, and 58 microliths. Thus it is likely that as the bags disintegrated over time, pieces fell out, and museum curators returned them to the remaining bags. It is essentially impossible, therefore, to do a comparison of the

modern assemblage housed in the NMT with that studied by Inskeep, and no real sense of

attrition can be determined. However it is safe to say that the assemblage underwent a

serious degree of mixing. Therefore it was determined that the best way to proceed with

analysis was to conduct a technological study of cores and retouched pieces throughout

the sequence, and avoid discussion of assemblage percent composition or

presence/absence of attributes.

A second primary objective of this study was to understand the changing tool

production schemes through time as related to other Tanzanian MSA and LSA rock

shelters. One goal was to analyze microliths present in the lower levels (Spits XXV-

XIII). New radiocarbon dates (Tryon et al, in review) place these spits at >45 ka - ~35 ka.

Inskeep noted backed pieces in these spits (Inskeep types 2, 3, and 4) in very low frequencies (n < 10). A quantitative analysis of these pieces would help examine the likelihood that these pieces moved down sequence from higher units. If morphometrically distinct from backed pieces in higher units, this analysis would be comparable to other sites with pre- 35 ka backed pieces, including Bed V at Mumba. However, after scanning the entire assemblage at the NMT for these rare backed pieces (n < 10) it became clear

229 that very few of the retouched tools from these lower levels are still present, with the exception of 10 scrapers in Spit XXII. Thus it is likely that the microliths reported by

Inskeep are not housed at the NMT in Dar es Salaam. The only other retouched tools older than 35 ka are derived from Spit XVIII, identified by Inskeep as Type 29 or “sinew frayers”.

Sinew frayers became one of the most complicated aspects of this re-analysis.

L.S.B. Leakey (1931) originally coined the term, based on his observations of local hunter-gatherers processing sinew:

“The essential character of this tool are as follows—it is made on a blade, and the direction of the working edge is more or less at right angles to the length of the blade, and the secondary trimming is towards the lower or main flake surface of the implement and forming a wide angle with it. The working edge of the tool is always somewhat rough and irregular, and frequently, after the tool has been made, one or more small flakes have been struck from the working-edge end of the tool on the multi-flake side, with the apparent intention of roughening the working edge.” (Leakey 1931: 99-100).

Leakey referred to the pieces as “sinew frayers” because he observed locals removing sinew from the legs and backs of animals, placing it on a piece of wood, and then scratching it with a jagged piece of metal or bone such that the sinew was frayed and

“the threads can be pulled off”. According to Leakey, this same method is also

“frequently applied to sisal and sanseveira by natives who wish to get the fibre from these plants for making thread and string” (1936: 100). Leakey admits to the vagaries of determining function from tool form, but notes that “sinew frayers” occurred most often in the same part of the cave as bone awls, suggesting a potential connection between the two.

However within the Kisese II assemblage, there was a stark difference between what Leakey originally defined as sinew frayers and what Inskeep later identified as

230 sinew frayers. This is odd because Inskeep directly communicated with Leakey about the

Kisese II excavation multiple times, one example of which is published in the

proceedings of the 1959 Pan African Congress (Inskeep, 1962). Leakey’s definition of

sinew frayers is essentially a truncated-faceted blade (Newcomer and Hivernel-Guerre,

1974), considered by others to be similar to Kostenki knives (McPherron, 2009). In re- analyzing the NMT Kisese II assemblage however, and given the available notes from

Inskeep’s archives, it became clear that Inskeep’s definition of sinew frayers were not blade-based at all, but rather they were made on cores.

Despite the inherent mixing discussed above, there is evidence of several pieces

(n = 97) in the NMT assemblages assigned to “T. 29” “sinew frayers”. At first glance these could be considered “high-backed scrapers” but upon further inspection a technological pattern was observed. These are modified pebbles that likely initiated discoidally. They are substantially thick and globular, averaging less than 2.5cm in diameter and ~1.5cm in thickness. On one face, two or more retouching flakes were removed such that the resulting aris was protruding and steep, forming a jagged or toothed edge. Occasionally the second removal was a truncation, forming a pointed apex or ‘perforator’. The resulting toothed edge or perforator was often characterized by spin- off fractures, burination spalls, or edge nibbling. This roughened and jagged edge is similar in some ways to the working edge of the truncated-faceted blade described by

Leakey (1931).

In this light, it is no surprise that Inskeep also defined a category of tools called

“micro-core tools”. Unfortunately there are currently only three bags labeled “T. 22” in the NMT assemblage, all of which contain an amalgamation of scaled pieces, backed

231 blades, unretouched flakes, burins, and even unworked crystals. It appears that these bags

are the result of mixing and that the micro-core tools Inskeep described are no longer housed at the NMT.

Figure B-9. Pieces described in the text as ‘sinew frayers’. In summary, the sinew frayers and micro core tools appear to be a unique component of the assemblage, having not been observed at any other quartz-dominated

MSA/LSA site in East Africa, and may represent a shift in technology at Kisese II.

According to Inskeep, the micro-core tools were only found in Spits XXI-XVI, with a

small occurrence in Spit XXIII, 14C dated to ~35-45 ka. Incidentally, these tools co-occur

with the earliest OES beads at Kisese II, in Spits XX and Spits XIX. However until a

formal analysis of more of Inskeep’s micro-tool cools is carried out, the existence of these tools and their implications remain speculative. Sinew frayers, according to

Inskeep’s archive and confirmed with this analysis, were found in Spits XXIII-XIV, with

232 a minor occurrence in Spit XXV, all 14C dated to >45 ka. If the regression line is

extended, and a constant deposition rate is assumed, it is possible that Spits XXIII-XIV, and therefore the “sinew frayers”, date somewhere between 60-50 ka. Additional sinew frayers were found throughout the upper part of the sequence from Spits IX-III, 14C dated

to 22-17 ka. The intermittent appearance of these tools, despite a continuous presence of

OES beads after 35 ka, may suggest a functional need that was not always present. A

similar pattern is seen for thumbnail scrapers, although these were not intensively studied

in this analysis.

In terms of core reduction strategy, Inskeep recognized discoidal, single platform,

bipolar, “nobbly”, and keeled cores. Nobbly cores were later re-named “amorphous”, and

refer to a migrating-plane multi-platform approach, whereas discoidal, and keeled cores

both involve organization into two flaking faces. Keeled cores refer to the removal of two

flakes from a common edge on opposing faces. Inskeep’s archives indicate,

unsurprisingly, that amorphous cores were the most common throughout the sequence.

This is likely due to the ‘catch-all’ nature of the category. Frequencies of the other core

types, however, suggest interesting patterns. Both discoids and keeled cores, as well as

single platform cores, decrease and/or disappear between Spit XVI and Spit XI. This

interval is one of the most poorly dated as yet; Spit XVI was not directly dated but

overlying Spit XV was 14C dated to ~35 ka. Spit XI was also not dated directly, but Spit

XII is dated to ~34 ka while Spit IX at ~22 ka. Thus it is likely that this dip in discoids,

keeled cores, and single platform cores occurred slightly before or near ~35 ka, but more

dating is required to determine the youngest extent of this gap. At this exact interval,

233 however, there was concurrently a major uptick in amorphous cores, despite absence of

all other core types. Spit XI also shows the first evidence of microliths at Kisese II.

A lack of cortical flakes and unexhausted cores implies that the earlier stages of

the reduction scheme are not sampled at Kisese II, although it is possible that cortical

flakes were lost or discarded. Rather, core reduction strategy had to be gleaned largely

from final core form only. With only these final stage cores, a qualitative study of core

reduction strategy was carried out, irrespective of Inskeep’s typology. The overwhelming

majority of cores showed an ad hoc approach, with cores having 3 or more working

faces, each with only one removal. Another notable observation was the use of both

bipolar and non-bipolar direct percussion within a single reduction sequence. On several specimens the pebbles were first “opened” with a bipolar split, as evidenced by crushing

on opposing edges, and then flaked centripetally on only one face. It is likely that this

fluid use of both bipolar and direct percussion is what enabled knappers to create

platform and small blade cores. Finally, one large unworked cobble exhibited removals

along the natural edge of the cobble, suggesting exploitation of natural core form, and the

possible initiation for discoidal reduction.

Overall, however, the lack of complete flakes, combined with a large degree of

mixing and attrition, imply that very few definitive conclusions can be made about core

reduction strategies at Kisese II. It is possible that the site was not a place for blank

production but rather tool refinement, retouch, and use. When comparing the NMT

collection side by side with Inskeep’s archived notes, a central conclusion is the

following: Inskeep’s “high-backed scrapers”, “keeled cores”, “micro core tools”, and

“sinew frayers” all represent a propensity to create durable, thick, and jagged or toothed

234 edges, sometimes retouched to form awls or perforators. While little can be conclusively determined from the assemblage in terms of lithic technology through time, it is likely that these jagged and durable edges represented a new manufacturing need, possibly hide working or OES production, and were outside the realm of ‘hunting technology’ so commonly discussed in MSA and LSA assemblages.

Table B-3. Inventory of Kisese lithics present in the NMT. Spit Number of Lithics I 206 Ib 5 II NA III 436 IV 366 IX 103 V 121 VI 38 VI, Ib, 4 XIV VII 130 VIII 156 X 162 XI 53 XII 30 XIII 64 XIV 26 XIX 52 XV 112 XVI 119 XVII 89 XVIII 32 XX 67 XXI NA XXII 43 XXV 12 XXVI 40 XXVII 43 XXVIII 34

235

B.4. Lukenya Hill – GvJm16

Lukenya Hill (−1.48°N, 37.0°E) is a Precambrian gneiss inselberg spanning 8km

in length and 2km in width, and is located in Machakos 200m above the Athi-Kapithi plains (Merrick 1975). The hill is covered by multiple rock shelters, several of which have been excavated over the last few decades. R. Gramly carried out initial excavations at eight shelters from 1970-1971, with a focus on GvJm22 (Gramly, 1976). Gramly considered the material from GvJm22 “LSA”, and in his survey reported another site,

GvJm16, which seemed to span the “MSA” and “LSA”. In 1971 Merrick returned to

GvJm16 and excavated it.

GvJm16 consists of two rock shelters, an upper and lower shelter. In the lower shelter Merrick placed a 1x6m trench through the talus slope into the shelter, and excavated 6.5m2 of sediment inside the shelter. At the upper shelter he placed a 2.5x1m

trench cross-cutting the inside of the shelter perpendicular to the back wall. He excavated

using a combination of 5cm spits and natural strata. In many cases he combined low-

density spits into 10cm spits for analytical purposes. Merrick divided the geology into

three major units: Bed A, B, and C. Like Anthony, Merrick described the geological and

occupational history of GvJm16 as a series of phases. Phase 1, the “protoshelter”, formed

Bed A sediments and accumulation of MSA artifacts. During Phase 2, according to

Merrick, there was a major roof collapse, forming the distinct upper and lower shelters,

and the appearance of “LSA” artifacts and formation of Bed 2. Phase 2 dates between 16,

750 and 13,510 BP (Merrick 1975). Bed C contained several potsherds and is though to

have been deposited with the last few millennia.

236 Merrick describes a decrease in quartz from the base of the sequence to the top, and an increase in obsidian over time. Quartz was likely obtained in the form of vein quartz from the Lukenya Hill basement system. Therefore this dataset consists of quartz artifacts from Unit A at GvJm16. Points in this unit are rare (2.2% of Merrick’s total

‘trimmed pieces’). Merrick divided the cores into “formal”, which had 4 flake scars or more, and “casual”, which had only three or less scars. Perhaps unsurprisingly, Merrick described the “formal” cores as lacking standardization.

Figure B-10. Idealized section of GvJm16 from Merrick 1975.

237 Lukenya Hill Reanalysis Results

The Lukenya Hill study assemblage comprised only GvJm16 Bed A. Merrick

describes Bed A as the lowermost excavated unit and containing “toolkits of M.S.A.

aspect” (Merrick, 1975:33). The date of these materials remains unknown, although

Merrick reports a “guess date in the range of 25,000 B.P. at least” (Merrick, 1975:53)

based on two radiocarbon samples (13,150 ± 200 and 16,750 ± 200) in Basal Bed C.

The Lukenya Hill material was studied over the course of a few days. As such the

sample size is not very large, comprising a total of 28 pieces derived from Merrick’s

assemblage labeled “formal quartz cores” (Table B-4). Because these layers at Lukenya

Hill are not well dated, this analysis focused on core reduction strategy as opposed to linear flake measurements. Cores (n=17) were measured, and 28 were captured for photogrammetric 3D analysis.

Figure B-11. Stratigraphic section of the northern wall of GvJm16, from Merrick (1975). Table B-4. Measured lithic dataset from GvJm16A (Lukenya Hill).

Provenience Complete Flake Core Flake Fragment Retouched Grand Total Piece X1 (see Table B-4) 4 17 2 5 28

Table B-5. Raw material composition of GvJm16 Industry A reported by Merrick 1975.

Raw Trimmed Untrimmed Flake Frequency of Raw Cores Total Material Pieces Fragments Material

238 Chert 40 60 2973 3073 18.64 Obsidian 44 25 1320 1389 8.42 Quartz 264 238 11246 11748 71.24 Other 1 7 272 280 1.70 Total 349 330 15811 16490 --

100% 90% 80% 70% 60% Other 50% Quartz 40% Obsidian 30% Chert 20% 10% 0% Trimmed Pieces Cores Untrimmed Flakes and Frag's

Figure B-12. Raw material composition of GvJm16 Industy A reported by Merrick 1975. All of the pieces studied were quartz and Merrick reported that quartz comprised

71.24% of the Industry A assemblage (Figure B-12). Three of the pieces were very rolled, calling into question the integrity of the assemblage. Merrick notes that Bed A was deposited within a “proto-shelter” prior to a major roof collapse that occurred ~16-

14,000BP. After the roof collapsed, forming the lower and upper shelters, large volumes of water poured into the site through a crack in the new roof of the lower shelter. This drainage removed the upper part of Bed A and apparently concentrated fossils and artifacts along the sides of the eroded Bed A deposits (Merrick, 1975). Later drainage traveled through a calcite enriched catchment before filtering down the crack in the roof,

239 bringing in water charged with CaCO3 and thus calcifying and cementing some of the

Bed A deposits. The rolled nature of these artifacts and the significant post-depositional alteration to Bed A indicates that they are likely very time-averaged, and technological behaviors at the site can only be coarsely studied.

Table B-6. Bins used to compare Mehlman and Merrick’s core orientations.

Core Orientations Peripheral Platform Amorphous (Mehlman) Core • Discoid • Single platform – • Irregular Typology • Approaching discoid prismatic Bins of • Approaching Levallois • Single platform – Merrick’s pyramidal data • Multiple platform • Double platform – alternate end • Double platform – other

240 100% 90% 80% 70% 60% %Amorphous 50% %Peripheral 40% %Bipolar 30% %Platform 20% 10% 0% Chert Obsidian Quartz Other

Figure B-13. Core orientations by raw material at GvJm16A as reported by Merrick 1975.

100% 90% 80% 70% 60% %Peripheral 50% %Bipolar 40% %Platform 30% 20% 10% 0% Chert Obsidian Quartz

Figure B-14. Core orientations of GvJm16A with “amorphous” and “other” raw material omitted. Considering the high proportion of quartz, there was surprisingly little evidence of bipolar in the GvJm16A studied assemblage, and this was confirmed by Merrick’s

241 analysis of the entire assemblage. Figure B-13 shows core morphology in Unit X1 of Bed

A, binned to parallel the frequencies of core orientation reported by Mehlman at Nasera

(Table B-6). Peripheral cores included Merrick’s “discoid”, “approaching discoid”, and

“approaching Levallois” counts, whereas Platform included Merrick’s “single platform

prismatic”, “single platform pyramidal”, “double platform alternate end”, “double

platform other”, and “multiple platform”. Figure B-14 shows these frequencies with the amorphous category omitted. The observations from the re-analysis, combined with these data from Merrick, indicate that despite a majority of the assemblage being comprised of quartz, Lukenya Hill foragers did not use bipolar to the extent of that seen at other quartz- dominated assemblages in the MSA and LSA. Obsidian and chert was predominantly worked with a platform approach whereas quartz was flaked both centripetally and with a platform approach in almost equal proportions (Figure B-14) but not with bipolar.

However, because final core form is not fully representative of total blank production strategy, these results should be confirmed from further study of flakes. Also it is possible that bipolar cores were overlooked by Merrick and exist elsewhere in the assemblage, and were not observed in this re-analysis. Overall it appears that, unlike Nasera, core reduction strategy at GvJm16A was not strongly correlated to raw material.

242 Appendix C. Lithic Analysis Definitions

Table C-1. Definitions utilized in the lithic analyses. These definitions were used in conjunction with and adapted from Wilkins, et al. (2017) and are the basis for the configuration (.CFG) file used in E4 coding (McPherron and Dibble, 2003). Reference for Code Name Condition Menu Definition specifics of measurement Enter Unique UniqueID Unique ID - Unique ID number - ID Enter lot Smallest unit of Lot Lot - - number provenience information Select the Name of researcher Researcher Researcher - - Researcher: analyzing lithic Quartzite Basalt Silcrete Quartz Raw Crystalline - RawMaterial - Material Quartz Ignimbrite Chert Chalcedony Other Other raw ID or describe raw material material ID OtherRaw MaterialID Condition1=RawMaterial Other - if “Other” was selected - or above description Complete flake with bulb, platform, distal end, clear CompFlake dorsal and ventral surfaces Lithic and no major breaks LithicArtifactClass Artifact Incomplete flake, with - Class clear dorsal and ventral FlakeFrag surfaces. Bulb and platform may or may not be present, flake is broken

243 Blade or blade fragment. Blank length is twice the width (this has to be estimated for fragments). Bladebladefrag Parallel or nearly parallel dorsal scars and lateral edges are expected. If in doubt go with flakefrag Artifact with no bulb and it is not possible to distinguish clear dorsal Shatter side and ventral surfaces. It should be chosen for all pieces in doubt Any piece with retouch - Retouched fairly continuous series of

Piece small removals along an edge Any piece that has had one or more blank removals (at Core least one negative bulb of percussion is visible) Hammerstone, Lithic artifact that has not manuport or been knapped grindstone Complete artifact is present Complete (also acceptable with some minor snaps or damage) Preserves complete bulb Proximal and platform but not the Condition1=LithicArtifactClass Completenes distal end Completeness NOT CompFlake Shatter Core - s Distal portion of detached HammerManuportGrindstone Distal piece, no platform or bulb Mesial portion of detached Mesial piece. No platform, bulb, or distal end Fragment Fragment - not possible to

244 say with confidence which part of the flake it represents Preserves left portion of platform and bulb, flake or Left lateral blade is split along flaking axis Preserves right portion of platform and bulb, flake or Right lateral blade is split along flaking axis Proximal Left

Lateral Proximal Right

Lateral Distal Left

Lateral Distal Right

Lateral Mesial Left

Lateral Mesial Right

Lateral Complete core or Complete hammer/grindstone/manup Core, ort Condition1=LithicArtifactClass CoreHammerCompleteness hammer A part of a core or - Core HammerManuportGrindstone completeness hammer/grindstone/manup Splitfragment ort that appears to have split or broke Condition1=LithicArtifactClass Artifact has two clear CompFlake Core opposed bulbs on the Evidence of HammerManuportGrindstone OR ventral surface, or two EvidenceBipolarPercussion bipolar Yes - Condition2=Completeness opposed negative bulbs percussion Complete LeftLateral RightLateral within a single dorsal or SplitHammerCobble flake scar

245 Artifact does not have any indication of being a No product of bipolar percussion Artifact is difficult to Indeterminate classify - maybe bipolar 0% Amount of cortex on 1-20% dorsal surface of flakes and 21-40% blades, and the blanks of 41-60% retouched pieces. For 61-80% shatter without 81-99% distinguishable dorsal and ventral faces it is the amount on the entire surface (not just dorsal). CortexArea Cortex area For cores it is the amount of cortex on each face

100% Enter the Estimated Cortex Area of DORSAL surface, or the entire surface of Shatter Core and HammerManuportGrindsto ne Condition1=LithicArtifactClass Present Platform is completely CompFlake OR complete cortical Platform Condition2=Completeness Platform is partially PlatformCortex Present partial - Cortex Complete Proximal LeftLateral cortical RightLateral ProxLeftLat There is no cortex on the Absent ProxRightLat platform Cortex Whole dorsal Condition1=CortexArea NOT 0% Location Proximal AND (complete Indicate where the majority Condition2=LithicArtifactClass Distal CortexLocation list also of cortex is present in the - NOT Shatter Core Right lateral includes dorsal surface HammerManuportGrindstone Left lateral proxleftlat

proxrightlat Midsection

246 distalleftlat distalrightlat mesialleftlat mesialrightla t) Condition1=LithicArtifactClass NOT Shatter Core Number of dorsal flake Dorsal Scar HammerManuportGrindstone DorsalScarCount - scars greater than 6 mm in - Count AND maximum length Condition2=CortexArea NOT 100%

Three or more scars from Radial at least three different directions

Condition1=LithicArtifactClass Two or more scars from NOT Shatter Core Subradial different non-opposed HammerManuportGrindstone directions AND Two or more scars from Bidirectional Dorsal Condition2=RetouchedPieceBlank two opposed directions DorsalDirection - Direction NOT ShatterIndeterminate AND Two or more scars from Unidirectional Condition3=CortexArea NOT one direction 100% AND Two or more scars from Condition4=DorsalScarCount NOT parallel directions but it is 0 1 Bi or not possible to determine Unidirectional whether they are bidirectional or unidirectional Indeterminate Difficult to classify Condition1=DorsalDirection Arisses are parallel or sub- Parallel Bidirectional Unidirectional parallel BiOrUni AND Convergent Arrisses are converge Aris ArisOrientation Condition2=CortexArea NOT - orientation 100% AND Indeterminate Condition3=DorsalScarCount NOT 0 1 2

247 Condition1=LithicArtifactClass CompFlake OR Condition2=Completeness (Andrefsky, CurvatureAngle Angle Depth Complete Proximal LeftLateral Numeric 1986) RightLateral ProxLeftLateral ProxRightLat

Mass Mass - Weight in grams - Maximum MaxLength - Maximum dimension - Length Maximum dimension Maximum MaxWidth - perpendicular to maximum - Width length Length from percussion point (or center of platform if not visible) to the distal Condition1=LithicArtifactClass end of the blank along (Debénath and Technologic CompFlake OR TechLength - flaking axis. In cores, the Dibble, 1993); al Length Condition2=Completeness length is measured along 19, method 3 Complete LeftLateral RightLateral axis of last flake/blade removal on surface with the most flake scars Condition1=LithicArtifactClass Technologic Maximum width (Debénath and CompFlake OR MaxTechWidth al Maximum - perpendicular to the Dibble, 1993); Condition2=Completeness Width technological length 19, method 2 Complete Proximal Mesial Max Maximum thickness MaxThickness - - Thickness including bulb Condition1=LithicArtifactClass Mid CompFlake OR Thickness at midpoint of MidThickness - - Thickness Condition2=Completeness technological length Complete LeftLateral RightLateral Condition1=LithicArtifactClass The distance between two (Debénath and Platform CompFlake OR points at which the striking PlatformWidth - Dibble, 1993); Width Condition2=Completeness platform intersects the 19, method 3 Complete Proximal ventral surface

248 Condition1=LithicArtifactClass The distance between the CompFlake OR point of percussion and the (Debénath and Platform Condition2=Completeness opposite point on the PlatformThickness - Dibble, 1993); Thickness Complete Proximal LeftLateral dorsal edge of the striking 19 RightLateral ProxLeftLat platform and the flake ProxRightLat dorsal surface Condition1=LithicArtifactClass Angle of platform and CompFlake OR Exterior dorsal surface take at Condition2=Completeness (Dibble and ExteriorPlatAngle Platform - platform midpoint and with Complete Proximal LeftLateral Bernard, 1980) Angle the arm of the goniometer RightLateral ProxLeftLat parallel to flake profile ProxRightLat Acute angle, sharp (Figure Feather a) In profile, termination hinged (Figure b) or Partial stepped (Figure c) on the hinge/step ventral side and is feathered on the dorsal side Condition1=LithicArtifactClass Abrupt right angle break CompFlake OR Step Flake (Figure c) FlakeTermination Condition2=Completeness Termination Difficult to classify if it is Complete Distal DistalLeftLat Hingeorstep either hinge or step DistalRightLat Preserves core relict edge or opposite platform, Overshoot plunging or not plunging (Figure d) (Andrefsky, Termination is difficult to 2005), p. 21) Indeterminate classify, or the artifact is retouched at distal end Condition1=LithicArtifactClass Plain platform, with only a Not prepared CompFlake OR single scar Condition2=Completeness More than one scar, Platform (Soriano, et al., PlatformPrep Complete Proximal LeftLateral Faceted (with negative bulbs of preparation 2007) RightLateral ProxLeftLat bulbs) percussion are visible ProxRightLat AND within at least one of them Condition3=PlatFormCortex NOT Residual More than one scar,

249 YesComplete faceting (no negative bulbs of bulbs) percussion are not visible Difficult to classify, may Indeterminate be due to crushing or very small thin size Condition1=LithicArtifactClass CompFlake OR Condition2=Completeness Enter number of Number of Complete Proximal LeftLateral platform scars NumberPlatformScars platform - - RightLateral ProxLeftLat (greater than scars ProxRightLat AND 1mm) Condition3=PlatformPrep NOT NotPrepared Indeterminate No small scars off the None platform on the dorsal face A cluster of small removals on the dorsal face Hinged with negative bulbs and removals hinged or stepped terminations that initiate of the platform Condition1=LithicArtifactClass A cluster of elongated CompFlake OR feather-terminating Long feather Dorsal Condition2=Completeness removals with negative (Soriano, et al., terminating DorsalPrep preparation Complete Proximal LeftLateral bulbs and hinged or 2007) removals RightLateral ProxLeftLat stepped terminations that ProxRightLat initiate of the platform Two clusters of small removals with negative bulbs and hinged or Lateral notching stepped terminations that initiate of the platform- one cluster near each lateral edge Indeterminate Difficult to classify Platform Condition1=LithicArtifactClass Narrow and linear (Soriano, et al., PlatformMorphology Narrow linear morphology CompFlake OR platform, see image D2 2007): 689

250 Condition2=Completeness Quadrangular or Broad thick platform, see Complete Proximal LeftLateral trapezoidal image D5 RightLateral ProxLeftLat Restricted platform , width Ovular or ProxRightLat is less than width of flake, triangular see image D3 Curved platform, see Curved image D4 Very small platform, see Punctiform image D1 Indeterminate Difficult to classify Condition1=LithicArtifactClass Small, generally isolated NOT Shatter Core Yes flake scars and/or snaps are HammerManuportGrindstone present on edges EdgeDamage Edge damage AND No Edge shows no damage - Condition2=Completeness NOT Fragment Indeterminate Difficult to classify

No DIFS present, though No diagnostic there may be snaps or other impact fracture types of breaks that are not 'diagnostic' Step-terminating fractures end abruptly and meet the surface of the flake at a right angle (Hayden 1979). Step Bending fractures initiate Diagnostic terminating Condition1=EdgeDamage Yes without the formation of a (Fischer, et al., DiagnosticImpactFractures impact bending fracture Hertzian cone and 1984) fractures consequently lack a negative bulb of percussion. Unifacialspinoff>6mm,Spi n-off fractures are cone Unifacial spin- fractures that initiate off off > 6mm bending fractures. Unifacial spin-off fractures occur only on one face, not

251 both. These fractures need to be more than 6 mm in max length to be considered difs (Fischer et al. 1984). Bifacialspinoff, Multiple spin-off fractures that Bifacial spin-off initiate off both faces of a bending fracture. Impact burinations resemble a burin blow occurring along either one Impact of the lateral edges, but burination lack the negative bulb of percussion common to deliberate burination. More than one type of DIF More than one is present. These will be type of DIF coded later in a seperate analysis. One or more convex half- moon modification to edge that was prepared with at least two small flake removals, or denticulation Notch/denticula is regular and exaggerated te (snaps or single flake Condition1=LithicArtifactClass removals are not RetouchType Retouch type RetouchedPiece considered notches but - should be coded as edge damage) Blunted edge(s) - very steep retouch, Backing perpendicular to plane of tool Probably rare - must have Burination negative bulb and located

252 along a lateral edge Invasive edge Long flake scars extend shaping into body of tool Short flake scars that do Marginal edge not extend into body of shaping tool Wedge shaped piece with Pieces several small stepped scars (Villa, et al., esquillees imitating from two 2012) opposed chisel-like edges Condition1=RetouchType Angle of retouched edge NotchDenticulate Backing (measure center of longest Retouched Enter angle of InvasiveEdgeShaping series of continuous - edge angle retouch. MarginalEdgeShaping retouch), or from inside the largest notch Enter the Condition1=RetouchType Diameter of Diameter of the Diameter of largest notch NotchDenticulate - largest notch Largest Notch on tool

(mm): Backed piece - Notched piece - Converging edges shaped Retouched point into a point Continuous retouch along a Side scraper portion of one lateral edge Continuous retouch that End scraper Retouched Condition1=LithicArtifactClass includes distal end piece RetouchedPiece Continuous retouch along - typology two edges that do not converge or converge into Double scraper a very thick or irregular point (would not be classified as a point) Scraper with three or more - edges retouched

253 Wedge shaped piece with Pieces several small stepped scars esquillees imitating from two opposed chisel-like edges Retouch is limited or edge damage may have resulted Minimally from use, difficult to retouched classify because there is so little retouch Difficult to classify because irregular or Indeterminate broken, but could be one of above categories Does not fit above category, but a typological designation is possible (i.e., transverse scraper, Other tanged tool, any other thing that might surprise us), if you pick this you will have to call it something in the next field Other Option to write in other retouched Condition1=RetouchedPieceTypol OtherRetouchedPieceTypology - typology if "other" is - piece ogy Other selected typology One face with one or more removals. Face 1 will be One the largest and/or most exploited face. Condition1=LithicArtifactClass Two faces with one or Number of NumberCoreFaces Core more removals. Face 1 will - core faces be the largest and/or most Two exploited face. Face 2 will be the next largest and/or most exploited face. Three Three faces with one or

254 more removals. Face 1 will be the largest and/or most exploited face. Face 2 will be the next largest and/or most exploited face. Face 3 will be the third largest and/or most exploited face. Four faces with one or more removals. Three faces with one or more removals. Face 1 will be the largest and/or most exploited face. Face 2 will Four be the next largest and/or most exploited face. Face 3 will be the third largest and/or most exploited face. Face 4 will be the fourth largest and/or most exploited face. More than four faces with one or more removals. MoreThanFour Details for only the first four faces will be recorded in this database. 0% 1-20% Condition1=LithicArtifactClass 21-40% Face X Core AND Amount of cortex on core FaceXCortexArea 41-60% - cortex area Condition2=CortexArea NOT 0% face 61-80%

81-99% 100% Condition1=LithicArtifactClass Number of dorsal flake Face X Scar FaceXDorsalScarCount Core - scars greater than 6 mm in - Count maximum length Face X Condition1=LithicArtifactClass Three or more scars from FaceXDorsalDirection Radial - Dorsal Core AND at least three different

255 Directionalit Condition2=Face1DorsalScarCoun directions y t NOT 0 1 Two or more scars from Subradial different non-opposed directions Two or more scars from Bidirectional two opposed directions Two or more scars from Unidirectional one direction Two or more scars from parallel directions but it's not possible to determine Bi or Uni whether they are bidirectional or unidirectional Indeterminate Difficult to classify Condition1=LithicArtifactClass Arisses more or less Parallel Core AND parallel Face X Aris FaceXArisOrientation Condition2=Face1DorsalDirection Convergent Arrisses converge - orientation NOT Radial Subradial Indeterminate Indeterminate NA Multiple removals of Recurrent relatively similar size One large removal that Condition1=LithicArtifactClass Preferential other removals may have Face X Core FaceXCoreExploitation Core been used to prepare for (Boëda, 1995) exploitation This face served mainly as the platform for Platform exploitation from a different core surface Feather Acute angle, sharp In profile, termination Face X Undulating or Condition1=LithicArtifactClass hinged or stepped on the Termination Partial FaceXTerminationFinalRemoval Core ventral side and is of final hinge/step feathered on the dorsal side removal Curved up towards the Hinge dorsal surface

256 Step Abrupt right angle break Preserves core relict edge Overshoot or opposite platform, plunging or not plunging Terminations that are difficult to classify, or Indeterminate piece is retouched at distal end Face X Condition1=LithicArtifactClass Length from bulb of Technologic FaceXLengthOfFinalRemoval Core - percussion to distal - al length of termination final removal Face X Condition1=LithicArtifactClass The technological width is Technologic FaceXWidthOfFinalRemoval Core - perpendicular to - al width of technological length final removal FaceXRemnantPlatformOfFinalRemo Final remnant platform is Not prepared val not prepared Face X Condition1=LithicArtifactClass Final remnant platform is Remnant Faceted Core faceted - platform of Final remnant platform is final removal Cortical cortical Indeterminate - Estimated core blank shape is sherical/cubical nodule Sphericalorcubi that would have had a low c surface area to volume ratio Estimated core blank shape Condition1=LithicArtifactClass Core blank is flat tabular nodule that CoreBlankSphericity Core - sphericity Notsphericalflat would have had a high

surface area to volume ratio Probably a flake blank based on visible or Flake partially visible bulbar surface

257 If in doubt go with Indeterminate indeterminate Enter Other OtherNotes OtherNotes - - Notes

258